{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "moving-breeding",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "运行中---------\n",
      "0\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[9.24 1.44]\n",
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      " [9.27 0.29]]\n",
      "<NDArray 80x2 @cpu(0)> \n",
      "[[3.43]\n",
      " [3.01]\n",
      " [4.4 ]\n",
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      " [6.06]\n",
      " [5.13]]\n",
      "<NDArray 80x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 8.388513\n",
      "epoch 2, loss 6.858780\n",
      "epoch 3, loss 5.632854\n",
      "epoch 4, loss 4.650396\n",
      "epoch 5, loss 3.863047\n",
      "epoch 6, loss 3.232057\n",
      "epoch 7, loss 2.726370\n",
      "epoch 8, loss 2.321099\n",
      "epoch 9, loss 1.996300\n",
      "epoch 10, loss 1.735989\n",
      "epoch 11, loss 1.527359\n",
      "epoch 12, loss 1.360145\n",
      "epoch 13, loss 1.226120\n",
      "epoch 14, loss 1.118694\n",
      "epoch 15, loss 1.032583\n",
      "epoch 16, loss 0.963553\n",
      "epoch 17, loss 0.908213\n",
      "epoch 18, loss 0.863842\n",
      "epoch 19, loss 0.828263\n",
      "epoch 20, loss 0.799729\n",
      "epoch 21, loss 0.776841\n",
      "epoch 22, loss 0.758477\n",
      "epoch 23, loss 0.743740\n",
      "epoch 24, loss 0.731908\n",
      "epoch 25, loss 0.722405\n",
      "epoch 26, loss 0.714769\n",
      "epoch 27, loss 0.708627\n",
      "epoch 28, loss 0.703685\n",
      "epoch 29, loss 0.699702\n",
      "epoch 30, loss 0.696490\n",
      "epoch 31, loss 0.693894\n",
      "epoch 32, loss 0.691793\n",
      "epoch 33, loss 0.690088\n",
      "epoch 34, loss 0.688700\n",
      "epoch 35, loss 0.687567\n",
      "epoch 36, loss 0.686638\n",
      "epoch 37, loss 0.685872\n",
      "epoch 38, loss 0.685237\n",
      "epoch 39, loss 0.684707\n",
      "epoch 40, loss 0.684262\n",
      "epoch 41, loss 0.683884\n",
      "epoch 42, loss 0.683560\n",
      "epoch 43, loss 0.683279\n",
      "epoch 44, loss 0.683033\n",
      "epoch 45, loss 0.682815\n",
      "epoch 46, loss 0.682619\n",
      "epoch 47, loss 0.682441\n",
      "epoch 48, loss 0.682278\n",
      "epoch 49, loss 0.682125\n",
      "epoch 50, loss 0.681983\n",
      "epoch 51, loss 0.681847\n",
      "epoch 52, loss 0.681718\n",
      "epoch 53, loss 0.681594\n",
      "epoch 54, loss 0.681473\n",
      "epoch 55, loss 0.681355\n",
      "epoch 56, loss 0.681240\n",
      "epoch 57, loss 0.681127\n",
      "epoch 58, loss 0.681016\n",
      "epoch 59, loss 0.680906\n",
      "epoch 60, loss 0.680797\n",
      "epoch 61, loss 0.680689\n",
      "epoch 62, loss 0.680581\n",
      "epoch 63, loss 0.680474\n",
      "epoch 64, loss 0.680368\n",
      "epoch 65, loss 0.680262\n",
      "epoch 66, loss 0.680156\n",
      "epoch 67, loss 0.680051\n",
      "epoch 68, loss 0.679946\n",
      "epoch 69, loss 0.679841\n",
      "epoch 70, loss 0.679736\n",
      "epoch 71, loss 0.679632\n",
      "epoch 72, loss 0.679527\n",
      "epoch 73, loss 0.679423\n",
      "epoch 74, loss 0.679319\n",
      "epoch 75, loss 0.679215\n",
      "epoch 76, loss 0.679111\n",
      "epoch 77, loss 0.679007\n",
      "epoch 78, loss 0.678903\n",
      "epoch 79, loss 0.678800\n",
      "epoch 80, loss 0.678696\n",
      "epoch 81, loss 0.678592\n",
      "epoch 82, loss 0.678489\n",
      "epoch 83, loss 0.678385\n",
      "epoch 84, loss 0.678282\n",
      "epoch 85, loss 0.678179\n",
      "epoch 86, loss 0.678076\n",
      "epoch 87, loss 0.677973\n",
      "epoch 88, loss 0.677870\n",
      "epoch 89, loss 0.677767\n",
      "epoch 90, loss 0.677664\n",
      "epoch 91, loss 0.677561\n",
      "epoch 92, loss 0.677458\n",
      "epoch 93, loss 0.677355\n",
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      "epoch 95, loss 0.677150\n",
      "epoch 96, loss 0.677048\n",
      "epoch 97, loss 0.676945\n",
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      "epoch 104, loss 0.676230\n",
      "epoch 105, loss 0.676128\n",
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      "epoch 110, loss 0.675620\n",
      "epoch 111, loss 0.675518\n",
      "epoch 112, loss 0.675417\n",
      "epoch 113, loss 0.675316\n",
      "epoch 114, loss 0.675214\n",
      "epoch 115, loss 0.675113\n",
      "epoch 116, loss 0.675012\n",
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      "epoch 118, loss 0.674810\n",
      "epoch 119, loss 0.674709\n",
      "epoch 120, loss 0.674608\n",
      "epoch 121, loss 0.674507\n",
      "epoch 122, loss 0.674407\n",
      "epoch 123, loss 0.674306\n",
      "epoch 124, loss 0.674205\n",
      "epoch 125, loss 0.674105\n",
      "epoch 126, loss 0.674004\n",
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      "epoch 128, loss 0.673804\n",
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      "epoch 143, loss 0.672306\n",
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      "epoch 145, loss 0.672108\n",
      "epoch 146, loss 0.672009\n",
      "epoch 147, loss 0.671910\n",
      "epoch 148, loss 0.671811\n",
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      "epoch 150, loss 0.671613\n",
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      "epoch 153, loss 0.671317\n",
      "epoch 154, loss 0.671218\n",
      "epoch 155, loss 0.671119\n",
      "epoch 156, loss 0.671021\n",
      "epoch 157, loss 0.670922\n",
      "epoch 158, loss 0.670824\n",
      "epoch 159, loss 0.670726\n",
      "epoch 160, loss 0.670627\n",
      "epoch 161, loss 0.670529\n",
      "epoch 162, loss 0.670431\n",
      "epoch 163, loss 0.670333\n",
      "epoch 164, loss 0.670235\n",
      "epoch 165, loss 0.670137\n",
      "epoch 166, loss 0.670039\n",
      "epoch 167, loss 0.669942\n",
      "epoch 168, loss 0.669844\n",
      "epoch 169, loss 0.669746\n",
      "epoch 170, loss 0.669649\n",
      "epoch 171, loss 0.669551\n",
      "epoch 172, loss 0.669454\n",
      "epoch 173, loss 0.669356\n",
      "epoch 174, loss 0.669259\n",
      "epoch 175, loss 0.669162\n",
      "epoch 176, loss 0.669065\n",
      "epoch 177, loss 0.668967\n",
      "epoch 178, loss 0.668870\n",
      "epoch 179, loss 0.668773\n",
      "epoch 180, loss 0.668676\n",
      "epoch 181, loss 0.668579\n",
      "epoch 182, loss 0.668483\n",
      "epoch 183, loss 0.668386\n",
      "epoch 184, loss 0.668289\n",
      "epoch 185, loss 0.668193\n",
      "epoch 186, loss 0.668096\n",
      "epoch 187, loss 0.668000\n",
      "epoch 188, loss 0.667903\n",
      "epoch 189, loss 0.667807\n",
      "epoch 190, loss 0.667710\n",
      "epoch 191, loss 0.667614\n",
      "epoch 192, loss 0.667518\n",
      "epoch 193, loss 0.667422\n",
      "epoch 194, loss 0.667326\n",
      "epoch 195, loss 0.667230\n",
      "epoch 196, loss 0.667134\n",
      "epoch 197, loss 0.667038\n",
      "epoch 198, loss 0.666942\n",
      "epoch 199, loss 0.666846\n",
      "epoch 200, loss 0.666751\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[ 0.48002774]\n",
      " [-0.03635949]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.05051063]\n",
      "<NDArray 1 @cpu(0)>\n",
      "1\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[9.19 2.29]\n",
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      " [9.3  3.14]]\n",
      "<NDArray 80x2 @cpu(0)> \n",
      "[[5.03]\n",
      " [2.61]\n",
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      " [5.  ]\n",
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      " [2.58]\n",
      " [3.49]\n",
      " [4.9 ]]\n",
      "<NDArray 80x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 6.210339\n",
      "epoch 2, loss 5.027859\n",
      "epoch 3, loss 4.099150\n",
      "epoch 4, loss 3.369749\n",
      "epoch 5, loss 2.796884\n",
      "epoch 6, loss 2.346961\n",
      "epoch 7, loss 1.993595\n",
      "epoch 8, loss 1.716063\n",
      "epoch 9, loss 1.498091\n",
      "epoch 10, loss 1.326898\n",
      "epoch 11, loss 1.192444\n",
      "epoch 12, loss 1.086843\n",
      "epoch 13, loss 1.003905\n",
      "epoch 14, loss 0.938766\n",
      "epoch 15, loss 0.887605\n",
      "epoch 16, loss 0.847423\n",
      "epoch 17, loss 0.815863\n",
      "epoch 18, loss 0.791076\n",
      "epoch 19, loss 0.771608\n",
      "epoch 20, loss 0.756317\n",
      "epoch 21, loss 0.744306\n",
      "epoch 22, loss 0.734873\n",
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      "epoch 34, loss 0.702220\n",
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      "epoch 39, loss 0.700868\n",
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      "epoch 42, loss 0.700565\n",
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      "epoch 44, loss 0.700452\n",
      "epoch 45, loss 0.700412\n",
      "epoch 46, loss 0.700379\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 47, loss 0.700353\n",
      "epoch 48, loss 0.700332\n",
      "epoch 49, loss 0.700314\n",
      "epoch 50, loss 0.700300\n",
      "epoch 51, loss 0.700288\n",
      "epoch 52, loss 0.700277\n",
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      "epoch 54, loss 0.700261\n",
      "epoch 55, loss 0.700254\n",
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      "epoch 57, loss 0.700242\n",
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      "epoch 59, loss 0.700232\n",
      "epoch 60, loss 0.700227\n",
      "epoch 61, loss 0.700223\n",
      "epoch 62, loss 0.700219\n",
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      "epoch 64, loss 0.700211\n",
      "epoch 65, loss 0.700207\n",
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      "epoch 78, loss 0.700159\n",
      "epoch 79, loss 0.700155\n",
      "epoch 80, loss 0.700152\n",
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      "epoch 82, loss 0.700145\n",
      "epoch 83, loss 0.700141\n",
      "epoch 84, loss 0.700138\n",
      "epoch 85, loss 0.700134\n",
      "epoch 86, loss 0.700130\n",
      "epoch 87, loss 0.700127\n",
      "epoch 88, loss 0.700123\n",
      "epoch 89, loss 0.700120\n",
      "epoch 90, loss 0.700116\n",
      "epoch 91, loss 0.700113\n",
      "epoch 92, loss 0.700109\n",
      "epoch 93, loss 0.700106\n",
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      "epoch 95, loss 0.700099\n",
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      "epoch 97, loss 0.700091\n",
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      "epoch 100, loss 0.700081\n",
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      "epoch 105, loss 0.700063\n",
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      "epoch 116, loss 0.700025\n",
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      "epoch 118, loss 0.700018\n",
      "epoch 119, loss 0.700014\n",
      "epoch 120, loss 0.700011\n",
      "epoch 121, loss 0.700007\n",
      "epoch 122, loss 0.700004\n",
      "epoch 123, loss 0.700000\n",
      "epoch 124, loss 0.699997\n",
      "epoch 125, loss 0.699993\n",
      "epoch 126, loss 0.699990\n",
      "epoch 127, loss 0.699986\n",
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      "epoch 129, loss 0.699979\n",
      "epoch 130, loss 0.699976\n",
      "epoch 131, loss 0.699972\n",
      "epoch 132, loss 0.699969\n",
      "epoch 133, loss 0.699965\n",
      "epoch 134, loss 0.699962\n",
      "epoch 135, loss 0.699959\n",
      "epoch 136, loss 0.699955\n",
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      "epoch 138, loss 0.699948\n",
      "epoch 139, loss 0.699945\n",
      "epoch 140, loss 0.699941\n",
      "epoch 141, loss 0.699938\n",
      "epoch 142, loss 0.699934\n",
      "epoch 143, loss 0.699931\n",
      "epoch 144, loss 0.699927\n",
      "epoch 145, loss 0.699924\n",
      "epoch 146, loss 0.699921\n",
      "epoch 147, loss 0.699917\n",
      "epoch 148, loss 0.699914\n",
      "epoch 149, loss 0.699910\n",
      "epoch 150, loss 0.699907\n",
      "epoch 151, loss 0.699904\n",
      "epoch 152, loss 0.699900\n",
      "epoch 153, loss 0.699897\n",
      "epoch 154, loss 0.699893\n",
      "epoch 155, loss 0.699890\n",
      "epoch 156, loss 0.699886\n",
      "epoch 157, loss 0.699883\n",
      "epoch 158, loss 0.699880\n",
      "epoch 159, loss 0.699876\n",
      "epoch 160, loss 0.699873\n",
      "epoch 161, loss 0.699869\n",
      "epoch 162, loss 0.699866\n",
      "epoch 163, loss 0.699863\n",
      "epoch 164, loss 0.699859\n",
      "epoch 165, loss 0.699856\n",
      "epoch 166, loss 0.699852\n",
      "epoch 167, loss 0.699849\n",
      "epoch 168, loss 0.699846\n",
      "epoch 169, loss 0.699842\n",
      "epoch 170, loss 0.699839\n",
      "epoch 171, loss 0.699835\n",
      "epoch 172, loss 0.699832\n",
      "epoch 173, loss 0.699829\n",
      "epoch 174, loss 0.699825\n",
      "epoch 175, loss 0.699822\n",
      "epoch 176, loss 0.699819\n",
      "epoch 177, loss 0.699815\n",
      "epoch 178, loss 0.699812\n",
      "epoch 179, loss 0.699808\n",
      "epoch 180, loss 0.699805\n",
      "epoch 181, loss 0.699802\n",
      "epoch 182, loss 0.699798\n",
      "epoch 183, loss 0.699795\n",
      "epoch 184, loss 0.699792\n",
      "epoch 185, loss 0.699788\n",
      "epoch 186, loss 0.699785\n",
      "epoch 187, loss 0.699782\n",
      "epoch 188, loss 0.699778\n",
      "epoch 189, loss 0.699775\n",
      "epoch 190, loss 0.699772\n",
      "epoch 191, loss 0.699768\n",
      "epoch 192, loss 0.699765\n",
      "epoch 193, loss 0.699762\n",
      "epoch 194, loss 0.699758\n",
      "epoch 195, loss 0.699755\n",
      "epoch 196, loss 0.699752\n",
      "epoch 197, loss 0.699748\n",
      "epoch 198, loss 0.699745\n",
      "epoch 199, loss 0.699742\n",
      "epoch 200, loss 0.699738\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.3647763 ]\n",
      " [0.11509058]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.03952941]\n",
      "<NDArray 1 @cpu(0)>\n",
      "2\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[9.2  5.44]\n",
      " [9.29 4.44]\n",
      " [9.24 4.44]\n",
      " [9.25 5.44]\n",
      " [9.19 5.14]\n",
      " [9.29 4.29]\n",
      " [9.2  4.14]\n",
      " [9.2  4.59]\n",
      " [9.19 5.29]\n",
      " [9.24 5.44]\n",
      " [9.3  5.44]\n",
      " [9.2  4.29]\n",
      " [9.24 4.14]\n",
      " [9.28 4.29]\n",
      " [9.24 4.59]\n",
      " [9.27 5.59]\n",
      " [9.27 5.44]\n",
      " [9.28 5.14]\n",
      " [9.25 4.29]\n",
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      " [9.26 5.29]\n",
      " [9.28 4.14]\n",
      " [9.19 4.59]\n",
      " [9.29 5.44]\n",
      " [9.25 5.14]\n",
      " [9.28 4.59]\n",
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      " [9.25 4.14]\n",
      " [9.27 4.59]\n",
      " [9.23 4.29]\n",
      " [9.23 5.59]\n",
      " [9.2  5.59]\n",
      " [9.2  4.44]\n",
      " [9.24 4.29]\n",
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      " [9.25 5.29]\n",
      " [9.19 4.44]\n",
      " [9.2  5.14]\n",
      " [9.27 4.29]\n",
      " [9.23 5.44]\n",
      " [9.25 4.44]\n",
      " [9.24 5.29]\n",
      " [9.3  5.14]\n",
      " [9.29 4.59]\n",
      " [9.29 5.29]\n",
      " [9.3  4.14]\n",
      " [9.3  5.59]\n",
      " [9.23 5.29]\n",
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      " [9.25 4.59]\n",
      " [9.19 5.44]\n",
      " [9.29 5.59]\n",
      " [9.28 5.59]\n",
      " [9.26 5.14]\n",
      " [9.28 5.29]\n",
      " [9.29 5.14]\n",
      " [9.23 5.14]\n",
      " [9.19 4.29]\n",
      " [9.29 4.14]\n",
      " [9.26 4.14]\n",
      " [9.28 5.44]\n",
      " [9.24 5.14]\n",
      " [9.27 4.44]\n",
      " [9.3  5.29]\n",
      " [9.26 4.59]\n",
      " [9.19 4.14]\n",
      " [9.23 4.44]\n",
      " [9.23 4.59]\n",
      " [9.24 5.59]\n",
      " [9.27 5.29]\n",
      " [9.26 4.44]\n",
      " [9.28 4.44]\n",
      " [9.3  4.44]\n",
      " [9.3  4.59]\n",
      " [9.27 5.14]\n",
      " [9.27 4.14]\n",
      " [9.3  4.29]]\n",
      "<NDArray 80x2 @cpu(0)> \n",
      "[[ 2.82]\n",
      " [ 5.33]\n",
      " [ 2.96]\n",
      " [ 5.02]\n",
      " [ 5.87]\n",
      " [ 4.61]\n",
      " [ 2.47]\n",
      " [ 3.26]\n",
      " [ 5.75]\n",
      " [ 4.87]\n",
      " [ 7.4 ]\n",
      " [ 2.36]\n",
      " [ 2.89]\n",
      " [ 4.34]\n",
      " [ 2.94]\n",
      " [ 7.53]\n",
      " [ 8.03]\n",
      " [ 7.07]\n",
      " [ 2.72]\n",
      " [ 4.95]\n",
      " [ 4.48]\n",
      " [ 4.67]\n",
      " [ 4.84]\n",
      " [ 6.46]\n",
      " [ 3.9 ]\n",
      " [ 4.83]\n",
      " [ 7.59]\n",
      " [ 2.84]\n",
      " [ 5.83]\n",
      " [ 3.57]\n",
      " [ 7.66]\n",
      " [ 4.78]\n",
      " [ 2.76]\n",
      " [ 2.74]\n",
      " [ 4.63]\n",
      " [ 2.5 ]\n",
      " [ 3.94]\n",
      " [ 2.96]\n",
      " [ 4.03]\n",
      " [ 4.86]\n",
      " [ 2.93]\n",
      " [ 4.82]\n",
      " [ 5.18]\n",
      " [ 2.96]\n",
      " [ 4.21]\n",
      " [ 6.47]\n",
      " [ 5.36]\n",
      " [ 7.19]\n",
      " [ 4.55]\n",
      " [20.57]\n",
      " [ 5.07]\n",
      " [ 8.26]\n",
      " [ 3.13]\n",
      " [ 7.77]\n",
      " [ 7.57]\n",
      " [ 8.45]\n",
      " [ 4.08]\n",
      " [17.5 ]\n",
      " [ 6.06]\n",
      " [ 5.14]\n",
      " [ 5.1 ]\n",
      " [ 4.66]\n",
      " [ 2.38]\n",
      " [19.02]\n",
      " [ 2.98]\n",
      " [ 4.25]\n",
      " [ 7.84]\n",
      " [ 2.92]\n",
      " [ 5.59]\n",
      " [ 2.52]\n",
      " [ 2.91]\n",
      " [ 6.75]\n",
      " [ 5.79]\n",
      " [ 3.16]\n",
      " [ 4.66]\n",
      " [ 4.49]\n",
      " [ 6.07]\n",
      " [ 7.22]\n",
      " [ 4.75]\n",
      " [ 4.54]]\n",
      "<NDArray 80x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 15.976880\n",
      "epoch 2, loss 13.220411\n",
      "epoch 3, loss 11.145267\n",
      "epoch 4, loss 9.583010\n",
      "epoch 5, loss 8.406844\n",
      "epoch 6, loss 7.521319\n",
      "epoch 7, loss 6.854581\n",
      "epoch 8, loss 6.352543\n",
      "epoch 9, loss 5.974485\n",
      "epoch 10, loss 5.689759\n",
      "epoch 11, loss 5.475292\n",
      "epoch 12, loss 5.313712\n",
      "epoch 13, loss 5.191945\n",
      "epoch 14, loss 5.100150\n",
      "epoch 15, loss 5.030915\n",
      "epoch 16, loss 4.978664\n",
      "epoch 17, loss 4.939199\n",
      "epoch 18, loss 4.909358\n",
      "epoch 19, loss 4.886762\n",
      "epoch 20, loss 4.869620\n",
      "epoch 21, loss 4.856584\n",
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      "epoch 26, loss 4.825047\n",
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      "epoch 30, loss 4.816669\n",
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      "epoch 38, loss 4.809766\n",
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      "epoch 40, loss 4.808574\n",
      "epoch 41, loss 4.808002\n",
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      "epoch 43, loss 4.806887\n",
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      "epoch 47, loss 4.804723\n",
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      "epoch 50, loss 4.803128\n",
      "epoch 51, loss 4.802598\n",
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      "epoch 57, loss 4.799436\n",
      "epoch 58, loss 4.798911\n",
      "epoch 59, loss 4.798386\n",
      "epoch 60, loss 4.797861\n",
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      "epoch 75, loss 4.790027\n",
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      "epoch 90, loss 4.782255\n",
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      "epoch 92, loss 4.781223\n",
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      "epoch 94, loss 4.780192\n",
      "epoch 95, loss 4.779678\n",
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      "epoch 114, loss 4.769946\n",
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      "epoch 126, loss 4.763850\n",
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      "epoch 129, loss 4.762331\n",
      "epoch 130, loss 4.761827\n",
      "epoch 131, loss 4.761321\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 132, loss 4.760816\n",
      "epoch 133, loss 4.760311\n",
      "epoch 134, loss 4.759807\n",
      "epoch 135, loss 4.759303\n",
      "epoch 136, loss 4.758799\n",
      "epoch 137, loss 4.758295\n",
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      "epoch 139, loss 4.757288\n",
      "epoch 140, loss 4.756785\n",
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      "epoch 142, loss 4.755781\n",
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      "epoch 150, loss 4.751771\n",
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      "epoch 154, loss 4.749773\n",
      "epoch 155, loss 4.749274\n",
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      "epoch 157, loss 4.748277\n",
      "epoch 158, loss 4.747779\n",
      "epoch 159, loss 4.747281\n",
      "epoch 160, loss 4.746783\n",
      "epoch 161, loss 4.746285\n",
      "epoch 162, loss 4.745789\n",
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      "epoch 164, loss 4.744795\n",
      "epoch 165, loss 4.744298\n",
      "epoch 166, loss 4.743803\n",
      "epoch 167, loss 4.743307\n",
      "epoch 168, loss 4.742811\n",
      "epoch 169, loss 4.742316\n",
      "epoch 170, loss 4.741821\n",
      "epoch 171, loss 4.741326\n",
      "epoch 172, loss 4.740832\n",
      "epoch 173, loss 4.740337\n",
      "epoch 174, loss 4.739843\n",
      "epoch 175, loss 4.739350\n",
      "epoch 176, loss 4.738856\n",
      "epoch 177, loss 4.738363\n",
      "epoch 178, loss 4.737870\n",
      "epoch 179, loss 4.737378\n",
      "epoch 180, loss 4.736885\n",
      "epoch 181, loss 4.736393\n",
      "epoch 182, loss 4.735901\n",
      "epoch 183, loss 4.735409\n",
      "epoch 184, loss 4.734918\n",
      "epoch 185, loss 4.734427\n",
      "epoch 186, loss 4.733936\n",
      "epoch 187, loss 4.733445\n",
      "epoch 188, loss 4.732955\n",
      "epoch 189, loss 4.732465\n",
      "epoch 190, loss 4.731975\n",
      "epoch 191, loss 4.731485\n",
      "epoch 192, loss 4.730996\n",
      "epoch 193, loss 4.730507\n",
      "epoch 194, loss 4.730018\n",
      "epoch 195, loss 4.729529\n",
      "epoch 196, loss 4.729041\n",
      "epoch 197, loss 4.728553\n",
      "epoch 198, loss 4.728065\n",
      "epoch 199, loss 4.727578\n",
      "epoch 200, loss 4.727090\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.37310615]\n",
      " [0.38897875]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.04060587]\n",
      "<NDArray 1 @cpu(0)>\n",
      "3\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[9.27 6.59]\n",
      " [9.2  7.29]\n",
      " [9.3  6.44]\n",
      " [9.19 6.29]\n",
      " [9.23 6.14]\n",
      " [9.24 6.44]\n",
      " [9.26 7.29]\n",
      " [9.29 6.29]\n",
      " [9.25 6.29]\n",
      " [9.3  7.44]\n",
      " [9.28 6.44]\n",
      " [9.2  6.59]\n",
      " [9.2  7.59]\n",
      " [9.25 7.44]\n",
      " [9.19 7.29]\n",
      " [9.26 7.44]\n",
      " [9.2  6.14]\n",
      " [9.2  6.44]\n",
      " [9.27 6.14]\n",
      " [9.19 6.14]\n",
      " [9.29 6.44]\n",
      " [9.3  6.14]\n",
      " [9.29 7.29]\n",
      " [9.3  7.14]\n",
      " [9.26 6.29]\n",
      " [9.27 7.59]\n",
      " [9.23 6.29]\n",
      " [9.26 7.14]\n",
      " [9.3  6.59]\n",
      " [9.24 6.59]\n",
      " [9.19 6.59]\n",
      " [9.19 7.14]\n",
      " [9.25 7.14]\n",
      " [9.24 7.29]\n",
      " [9.2  6.29]\n",
      " [9.19 7.59]\n",
      " [9.25 7.29]\n",
      " [9.25 6.14]\n",
      " [9.19 7.44]\n",
      " [9.26 6.59]\n",
      " [9.29 6.59]\n",
      " [9.29 7.59]\n",
      " [9.3  7.59]\n",
      " [9.19 6.44]\n",
      " [9.27 6.29]\n",
      " [9.23 6.44]\n",
      " [9.25 6.44]\n",
      " [9.28 7.44]\n",
      " [9.23 6.59]\n",
      " [9.27 7.44]\n",
      " [9.26 7.59]\n",
      " [9.28 6.29]\n",
      " [9.28 6.14]\n",
      " [9.25 7.59]\n",
      " [9.27 7.14]\n",
      " [9.28 7.59]\n",
      " [9.29 7.14]\n",
      " [9.24 6.14]\n",
      " [9.24 6.29]\n",
      " [9.23 7.44]\n",
      " [9.29 6.14]\n",
      " [9.28 6.59]\n",
      " [9.23 7.59]\n",
      " [9.2  7.14]\n",
      " [9.28 7.29]\n",
      " [9.27 6.44]\n",
      " [9.25 6.59]\n",
      " [9.24 7.59]\n",
      " [9.29 7.44]\n",
      " [9.3  6.29]\n",
      " [9.3  7.29]\n",
      " [9.23 7.14]\n",
      " [9.2  7.44]\n",
      " [9.24 7.44]\n",
      " [9.26 6.14]\n",
      " [9.27 7.29]\n",
      " [9.24 7.14]\n",
      " [9.26 6.44]\n",
      " [9.23 7.29]\n",
      " [9.28 7.14]]\n",
      "<NDArray 80x2 @cpu(0)> \n",
      "[[18.04]\n",
      " [10.37]\n",
      " [13.74]\n",
      " [ 9.12]\n",
      " [ 8.59]\n",
      " [14.13]\n",
      " [15.26]\n",
      " [12.04]\n",
      " [ 7.9 ]\n",
      " [15.34]\n",
      " [15.71]\n",
      " [ 8.78]\n",
      " [14.25]\n",
      " [14.72]\n",
      " [19.05]\n",
      " [18.9 ]\n",
      " [ 4.91]\n",
      " [ 8.13]\n",
      " [10.56]\n",
      " [ 8.55]\n",
      " [14.36]\n",
      " [20.8 ]\n",
      " [15.99]\n",
      " [20.88]\n",
      " [11.83]\n",
      " [15.09]\n",
      " [12.02]\n",
      " [14.88]\n",
      " [17.18]\n",
      " [28.88]\n",
      " [14.91]\n",
      " [12.5 ]\n",
      " [24.25]\n",
      " [17.16]\n",
      " [ 6.95]\n",
      " [15.87]\n",
      " [13.68]\n",
      " [ 9.38]\n",
      " [20.83]\n",
      " [11.35]\n",
      " [16.96]\n",
      " [14.72]\n",
      " [15.13]\n",
      " [12.94]\n",
      " [12.74]\n",
      " [17.18]\n",
      " [12.24]\n",
      " [15.03]\n",
      " [16.55]\n",
      " [16.02]\n",
      " [15.15]\n",
      " [15.76]\n",
      " [12.59]\n",
      " [15.17]\n",
      " [19.63]\n",
      " [13.29]\n",
      " [17.57]\n",
      " [ 9.32]\n",
      " [12.25]\n",
      " [15.62]\n",
      " [11.48]\n",
      " [15.57]\n",
      " [20.28]\n",
      " [ 9.44]\n",
      " [15.91]\n",
      " [15.5 ]\n",
      " [28.48]\n",
      " [15.59]\n",
      " [15.42]\n",
      " [14.14]\n",
      " [18.95]\n",
      " [16.88]\n",
      " [13.72]\n",
      " [16.79]\n",
      " [ 8.7 ]\n",
      " [19.18]\n",
      " [27.45]\n",
      " [12.67]\n",
      " [14.69]\n",
      " [17.66]]\n",
      "<NDArray 80x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 88.694000\n",
      "epoch 2, loss 65.231277\n",
      "epoch 3, loss 48.698334\n",
      "epoch 4, loss 37.048389\n",
      "epoch 5, loss 28.839228\n",
      "epoch 6, loss 23.054590\n",
      "epoch 7, loss 18.978376\n",
      "epoch 8, loss 16.105991\n",
      "epoch 9, loss 14.081873\n",
      "epoch 10, loss 12.655485\n",
      "epoch 11, loss 11.650280\n",
      "epoch 12, loss 10.941861\n",
      "epoch 13, loss 10.442567\n",
      "epoch 14, loss 10.090634\n",
      "epoch 15, loss 9.842536\n",
      "epoch 16, loss 9.667608\n",
      "epoch 17, loss 9.544237\n",
      "epoch 18, loss 9.457194\n",
      "epoch 19, loss 9.395750\n",
      "epoch 20, loss 9.352346\n",
      "epoch 21, loss 9.321653\n",
      "epoch 22, loss 9.299914\n",
      "epoch 23, loss 9.284488\n",
      "epoch 24, loss 9.273510\n",
      "epoch 25, loss 9.265665\n",
      "epoch 26, loss 9.260027\n",
      "epoch 27, loss 9.255946\n",
      "epoch 28, loss 9.252962\n",
      "epoch 29, loss 9.250751\n",
      "epoch 30, loss 9.249084\n",
      "epoch 31, loss 9.247800\n",
      "epoch 32, loss 9.246787\n",
      "epoch 33, loss 9.245965\n",
      "epoch 34, loss 9.245276\n",
      "epoch 35, loss 9.244683\n",
      "epoch 36, loss 9.244157\n",
      "epoch 37, loss 9.243677\n",
      "epoch 38, loss 9.243231\n",
      "epoch 39, loss 9.242808\n",
      "epoch 40, loss 9.242403\n",
      "epoch 41, loss 9.242007\n",
      "epoch 42, loss 9.241623\n",
      "epoch 43, loss 9.241242\n",
      "epoch 44, loss 9.240866\n",
      "epoch 45, loss 9.240493\n",
      "epoch 46, loss 9.240122\n",
      "epoch 47, loss 9.239754\n",
      "epoch 48, loss 9.239385\n",
      "epoch 49, loss 9.239018\n",
      "epoch 50, loss 9.238652\n",
      "epoch 51, loss 9.238286\n",
      "epoch 52, loss 9.237920\n",
      "epoch 53, loss 9.237555\n",
      "epoch 54, loss 9.237189\n",
      "epoch 55, loss 9.236825\n",
      "epoch 56, loss 9.236460\n",
      "epoch 57, loss 9.236095\n",
      "epoch 58, loss 9.235732\n",
      "epoch 59, loss 9.235368\n",
      "epoch 60, loss 9.235003\n",
      "epoch 61, loss 9.234640\n",
      "epoch 62, loss 9.234278\n",
      "epoch 63, loss 9.233914\n",
      "epoch 64, loss 9.233550\n",
      "epoch 65, loss 9.233188\n",
      "epoch 66, loss 9.232824\n",
      "epoch 67, loss 9.232462\n",
      "epoch 68, loss 9.232100\n",
      "epoch 69, loss 9.231737\n",
      "epoch 70, loss 9.231375\n",
      "epoch 71, loss 9.231013\n",
      "epoch 72, loss 9.230652\n",
      "epoch 73, loss 9.230289\n",
      "epoch 74, loss 9.229928\n",
      "epoch 75, loss 9.229567\n",
      "epoch 76, loss 9.229204\n",
      "epoch 77, loss 9.228845\n",
      "epoch 78, loss 9.228483\n",
      "epoch 79, loss 9.228123\n",
      "epoch 80, loss 9.227762\n",
      "epoch 81, loss 9.227402\n",
      "epoch 82, loss 9.227041\n",
      "epoch 83, loss 9.226682\n",
      "epoch 84, loss 9.226320\n",
      "epoch 85, loss 9.225962\n",
      "epoch 86, loss 9.225601\n",
      "epoch 87, loss 9.225243\n",
      "epoch 88, loss 9.224882\n",
      "epoch 89, loss 9.224524\n",
      "epoch 90, loss 9.224165\n",
      "epoch 91, loss 9.223805\n",
      "epoch 92, loss 9.223448\n",
      "epoch 93, loss 9.223088\n",
      "epoch 94, loss 9.222730\n",
      "epoch 95, loss 9.222372\n",
      "epoch 96, loss 9.222013\n",
      "epoch 97, loss 9.221655\n",
      "epoch 98, loss 9.221297\n",
      "epoch 99, loss 9.220940\n",
      "epoch 100, loss 9.220583\n",
      "epoch 101, loss 9.220225\n",
      "epoch 102, loss 9.219869\n",
      "epoch 103, loss 9.219511\n",
      "epoch 104, loss 9.219153\n",
      "epoch 105, loss 9.218798\n",
      "epoch 106, loss 9.218440\n",
      "epoch 107, loss 9.218084\n",
      "epoch 108, loss 9.217729\n",
      "epoch 109, loss 9.217373\n",
      "epoch 110, loss 9.217016\n",
      "epoch 111, loss 9.216660\n",
      "epoch 112, loss 9.216305\n",
      "epoch 113, loss 9.215949\n",
      "epoch 114, loss 9.215593\n",
      "epoch 115, loss 9.215239\n",
      "epoch 116, loss 9.214884\n",
      "epoch 117, loss 9.214529\n",
      "epoch 118, loss 9.214174\n",
      "epoch 119, loss 9.213820\n",
      "epoch 120, loss 9.213465\n",
      "epoch 121, loss 9.213111\n",
      "epoch 122, loss 9.212756\n",
      "epoch 123, loss 9.212403\n",
      "epoch 124, loss 9.212049\n",
      "epoch 125, loss 9.211695\n",
      "epoch 126, loss 9.211342\n",
      "epoch 127, loss 9.210989\n",
      "epoch 128, loss 9.210635\n",
      "epoch 129, loss 9.210282\n",
      "epoch 130, loss 9.209929\n",
      "epoch 131, loss 9.209578\n",
      "epoch 132, loss 9.209224\n",
      "epoch 133, loss 9.208871\n",
      "epoch 134, loss 9.208520\n",
      "epoch 135, loss 9.208167\n",
      "epoch 136, loss 9.207815\n",
      "epoch 137, loss 9.207463\n",
      "epoch 138, loss 9.207112\n",
      "epoch 139, loss 9.206760\n",
      "epoch 140, loss 9.206409\n",
      "epoch 141, loss 9.206058\n",
      "epoch 142, loss 9.205706\n",
      "epoch 143, loss 9.205356\n",
      "epoch 144, loss 9.205005\n",
      "epoch 145, loss 9.204655\n",
      "epoch 146, loss 9.204304\n",
      "epoch 147, loss 9.203954\n",
      "epoch 148, loss 9.203604\n",
      "epoch 149, loss 9.203253\n",
      "epoch 150, loss 9.202904\n",
      "epoch 151, loss 9.202554\n",
      "epoch 152, loss 9.202205\n",
      "epoch 153, loss 9.201855\n",
      "epoch 154, loss 9.201506\n",
      "epoch 155, loss 9.201157\n",
      "epoch 156, loss 9.200808\n",
      "epoch 157, loss 9.200459\n",
      "epoch 158, loss 9.200109\n",
      "epoch 159, loss 9.199762\n",
      "epoch 160, loss 9.199413\n",
      "epoch 161, loss 9.199065\n",
      "epoch 162, loss 9.198717\n",
      "epoch 163, loss 9.198370\n",
      "epoch 164, loss 9.198022\n",
      "epoch 165, loss 9.197674\n",
      "epoch 166, loss 9.197327\n",
      "epoch 167, loss 9.196980\n",
      "epoch 168, loss 9.196632\n",
      "epoch 169, loss 9.196286\n",
      "epoch 170, loss 9.195939\n",
      "epoch 171, loss 9.195592\n",
      "epoch 172, loss 9.195246\n",
      "epoch 173, loss 9.194899\n",
      "epoch 174, loss 9.194552\n",
      "epoch 175, loss 9.194206\n",
      "epoch 176, loss 9.193861\n",
      "epoch 177, loss 9.193515\n",
      "epoch 178, loss 9.193169\n",
      "epoch 179, loss 9.192823\n",
      "epoch 180, loss 9.192478\n",
      "epoch 181, loss 9.192133\n",
      "epoch 182, loss 9.191789\n",
      "epoch 183, loss 9.191442\n",
      "epoch 184, loss 9.191099\n",
      "epoch 185, loss 9.190754\n",
      "epoch 186, loss 9.190409\n",
      "epoch 187, loss 9.190065\n",
      "epoch 188, loss 9.189721\n",
      "epoch 189, loss 9.189377\n",
      "epoch 190, loss 9.189033\n",
      "epoch 191, loss 9.188689\n",
      "epoch 192, loss 9.188347\n",
      "epoch 193, loss 9.188003\n",
      "epoch 194, loss 9.187659\n",
      "epoch 195, loss 9.187316\n",
      "epoch 196, loss 9.186973\n",
      "epoch 197, loss 9.186630\n",
      "epoch 198, loss 9.186288\n",
      "epoch 199, loss 9.185946\n",
      "epoch 200, loss 9.185602\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.95719373]\n",
      " [0.8697491 ]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.10283697]\n",
      "<NDArray 1 @cpu(0)>\n",
      "4\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[9.24 8.44]\n",
      " [9.27 9.44]\n",
      " [9.27 9.14]\n",
      " [9.26 9.29]\n",
      " [9.29 9.29]\n",
      " [9.2  9.59]\n",
      " [9.29 8.59]\n",
      " [9.24 8.29]\n",
      " [9.3  9.29]\n",
      " [9.2  8.59]\n",
      " [9.29 8.44]\n",
      " [9.24 9.44]\n",
      " [9.19 9.29]\n",
      " [9.2  9.29]\n",
      " [9.28 9.29]\n",
      " [9.29 9.14]\n",
      " [9.26 9.14]\n",
      " [9.2  8.44]\n",
      " [9.23 9.44]\n",
      " [9.19 8.59]\n",
      " [9.29 9.59]\n",
      " [9.25 9.29]\n",
      " [9.24 9.59]\n",
      " [9.28 9.44]\n",
      " [9.27 8.59]\n",
      " [9.25 8.59]\n",
      " [9.28 8.29]\n",
      " [9.25 8.29]\n",
      " [9.29 8.29]\n",
      " [9.28 8.59]\n",
      " [9.27 8.29]\n",
      " [9.25 9.59]\n",
      " [9.28 9.14]\n",
      " [9.28 8.14]\n",
      " [9.26 9.44]\n",
      " [9.3  8.44]\n",
      " [9.3  9.44]\n",
      " [9.23 9.59]\n",
      " [9.19 8.29]\n",
      " [9.3  8.14]\n",
      " [9.19 9.14]\n",
      " [9.24 8.14]\n",
      " [9.27 8.44]\n",
      " [9.23 9.29]\n",
      " [9.24 8.59]\n",
      " [9.23 8.14]\n",
      " [9.23 8.59]\n",
      " [9.25 9.44]\n",
      " [9.27 9.59]\n",
      " [9.26 8.14]\n",
      " [9.27 9.29]\n",
      " [9.23 9.14]\n",
      " [9.3  9.59]\n",
      " [9.29 9.44]\n",
      " [9.19 8.14]\n",
      " [9.2  9.14]\n",
      " [9.26 8.59]\n",
      " [9.27 8.14]\n",
      " [9.3  8.59]\n",
      " [9.19 8.44]\n",
      " [9.24 9.29]\n",
      " [9.26 9.59]\n",
      " [9.23 8.29]\n",
      " [9.25 8.14]\n",
      " [9.3  8.29]\n",
      " [9.2  9.44]\n",
      " [9.2  8.14]\n",
      " [9.26 8.44]\n",
      " [9.25 8.44]\n",
      " [9.25 9.14]\n",
      " [9.29 8.14]\n",
      " [9.26 8.29]\n",
      " [9.3  9.14]\n",
      " [9.28 8.44]\n",
      " [9.19 9.59]\n",
      " [9.19 9.44]\n",
      " [9.28 9.59]\n",
      " [9.2  8.29]\n",
      " [9.23 8.44]\n",
      " [9.24 9.14]]\n",
      "<NDArray 80x2 @cpu(0)> \n",
      "[[12.67]\n",
      " [ 8.88]\n",
      " [11.51]\n",
      " [ 9.92]\n",
      " [10.13]\n",
      " [10.38]\n",
      " [10.13]\n",
      " [14.56]\n",
      " [10.39]\n",
      " [11.31]\n",
      " [14.45]\n",
      " [ 7.97]\n",
      " [28.05]\n",
      " [10.86]\n",
      " [ 9.61]\n",
      " [10.69]\n",
      " [13.05]\n",
      " [12.16]\n",
      " [ 5.78]\n",
      " [17.52]\n",
      " [10.29]\n",
      " [ 9.34]\n",
      " [ 8.6 ]\n",
      " [10.02]\n",
      " [22.97]\n",
      " [ 9.11]\n",
      " [13.1 ]\n",
      " [10.02]\n",
      " [10.03]\n",
      " [10.14]\n",
      " [14.32]\n",
      " [ 6.89]\n",
      " [ 9.64]\n",
      " [13.17]\n",
      " [11.93]\n",
      " [14.18]\n",
      " [ 7.67]\n",
      " [ 8.99]\n",
      " [18.4 ]\n",
      " [14.41]\n",
      " [15.31]\n",
      " [15.29]\n",
      " [25.05]\n",
      " [ 9.9 ]\n",
      " [11.55]\n",
      " [20.05]\n",
      " [ 8.09]\n",
      " [ 9.18]\n",
      " [11.55]\n",
      " [26.84]\n",
      " [10.17]\n",
      " [12.72]\n",
      " [ 8.56]\n",
      " [ 9.23]\n",
      " [17.5 ]\n",
      " [ 9.56]\n",
      " [14.53]\n",
      " [13.41]\n",
      " [10.83]\n",
      " [15.85]\n",
      " [ 9.19]\n",
      " [ 7.99]\n",
      " [ 9.72]\n",
      " [13.54]\n",
      " [14.9 ]\n",
      " [11.91]\n",
      " [13.78]\n",
      " [17.68]\n",
      " [10.89]\n",
      " [ 9.87]\n",
      " [14.  ]\n",
      " [19.92]\n",
      " [10.56]\n",
      " [12.62]\n",
      " [14.21]\n",
      " [26.62]\n",
      " [12.14]\n",
      " [15.17]\n",
      " [ 8.76]\n",
      " [10.29]]\n",
      "<NDArray 80x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 62.329445\n",
      "epoch 2, loss 43.954506\n",
      "epoch 3, loss 32.146088\n",
      "epoch 4, loss 24.557446\n",
      "epoch 5, loss 19.680529\n",
      "epoch 6, loss 16.546230\n",
      "epoch 7, loss 14.531776\n",
      "epoch 8, loss 13.236959\n",
      "epoch 9, loss 12.404594\n",
      "epoch 10, loss 11.869415\n",
      "epoch 11, loss 11.525213\n",
      "epoch 12, loss 11.303737\n",
      "epoch 13, loss 11.161127\n",
      "epoch 14, loss 11.069201\n",
      "epoch 15, loss 11.009841\n",
      "epoch 16, loss 10.971413\n",
      "epoch 17, loss 10.946434\n",
      "epoch 18, loss 10.930099\n",
      "epoch 19, loss 10.919317\n",
      "epoch 20, loss 10.912107\n",
      "epoch 21, loss 10.907190\n",
      "epoch 22, loss 10.903747\n",
      "epoch 23, loss 10.901251\n",
      "epoch 24, loss 10.899365\n",
      "epoch 25, loss 10.897870\n",
      "epoch 26, loss 10.896627\n",
      "epoch 27, loss 10.895545\n",
      "epoch 28, loss 10.894567\n",
      "epoch 29, loss 10.893658\n",
      "epoch 30, loss 10.892790\n",
      "epoch 31, loss 10.891951\n",
      "epoch 32, loss 10.891129\n",
      "epoch 33, loss 10.890319\n",
      "epoch 34, loss 10.889517\n",
      "epoch 35, loss 10.888720\n",
      "epoch 36, loss 10.887926\n",
      "epoch 37, loss 10.887133\n",
      "epoch 38, loss 10.886344\n",
      "epoch 39, loss 10.885553\n",
      "epoch 40, loss 10.884766\n",
      "epoch 41, loss 10.883978\n",
      "epoch 42, loss 10.883191\n",
      "epoch 43, loss 10.882404\n",
      "epoch 44, loss 10.881618\n",
      "epoch 45, loss 10.880831\n",
      "epoch 46, loss 10.880046\n",
      "epoch 47, loss 10.879260\n",
      "epoch 48, loss 10.878474\n",
      "epoch 49, loss 10.877690\n",
      "epoch 50, loss 10.876905\n",
      "epoch 51, loss 10.876122\n",
      "epoch 52, loss 10.875338\n",
      "epoch 53, loss 10.874552\n",
      "epoch 54, loss 10.873770\n",
      "epoch 55, loss 10.872987\n",
      "epoch 56, loss 10.872204\n",
      "epoch 57, loss 10.871420\n",
      "epoch 58, loss 10.870638\n",
      "epoch 59, loss 10.869856\n",
      "epoch 60, loss 10.869073\n",
      "epoch 61, loss 10.868292\n",
      "epoch 62, loss 10.867510\n",
      "epoch 63, loss 10.866729\n",
      "epoch 64, loss 10.865949\n",
      "epoch 65, loss 10.865168\n",
      "epoch 66, loss 10.864388\n",
      "epoch 67, loss 10.863607\n",
      "epoch 68, loss 10.862828\n",
      "epoch 69, loss 10.862048\n",
      "epoch 70, loss 10.861270\n",
      "epoch 71, loss 10.860491\n",
      "epoch 72, loss 10.859712\n",
      "epoch 73, loss 10.858933\n",
      "epoch 74, loss 10.858155\n",
      "epoch 75, loss 10.857378\n",
      "epoch 76, loss 10.856600\n",
      "epoch 77, loss 10.855823\n",
      "epoch 78, loss 10.855045\n",
      "epoch 79, loss 10.854269\n",
      "epoch 80, loss 10.853493\n",
      "epoch 81, loss 10.852716\n",
      "epoch 82, loss 10.851940\n",
      "epoch 83, loss 10.851164\n",
      "epoch 84, loss 10.850389\n",
      "epoch 85, loss 10.849614\n",
      "epoch 86, loss 10.848840\n",
      "epoch 87, loss 10.848065\n",
      "epoch 88, loss 10.847291\n",
      "epoch 89, loss 10.846517\n",
      "epoch 90, loss 10.845743\n",
      "epoch 91, loss 10.844969\n",
      "epoch 92, loss 10.844196\n",
      "epoch 93, loss 10.843424\n",
      "epoch 94, loss 10.842651\n",
      "epoch 95, loss 10.841878\n",
      "epoch 96, loss 10.841106\n",
      "epoch 97, loss 10.840334\n",
      "epoch 98, loss 10.839563\n",
      "epoch 99, loss 10.838791\n",
      "epoch 100, loss 10.838020\n",
      "epoch 101, loss 10.837250\n",
      "epoch 102, loss 10.836478\n",
      "epoch 103, loss 10.835709\n",
      "epoch 104, loss 10.834939\n",
      "epoch 105, loss 10.834168\n",
      "epoch 106, loss 10.833400\n",
      "epoch 107, loss 10.832630\n",
      "epoch 108, loss 10.831861\n",
      "epoch 109, loss 10.831094\n",
      "epoch 110, loss 10.830325\n",
      "epoch 111, loss 10.829557\n",
      "epoch 112, loss 10.828789\n",
      "epoch 113, loss 10.828021\n",
      "epoch 114, loss 10.827253\n",
      "epoch 115, loss 10.826488\n",
      "epoch 116, loss 10.825721\n",
      "epoch 117, loss 10.824953\n",
      "epoch 118, loss 10.824187\n",
      "epoch 119, loss 10.823422\n",
      "epoch 120, loss 10.822656\n",
      "epoch 121, loss 10.821891\n",
      "epoch 122, loss 10.821126\n",
      "epoch 123, loss 10.820361\n",
      "epoch 124, loss 10.819597\n",
      "epoch 125, loss 10.818832\n",
      "epoch 126, loss 10.818069\n",
      "epoch 127, loss 10.817305\n",
      "epoch 128, loss 10.816541\n",
      "epoch 129, loss 10.815778\n",
      "epoch 130, loss 10.815015\n",
      "epoch 131, loss 10.814253\n",
      "epoch 132, loss 10.813490\n",
      "epoch 133, loss 10.812727\n",
      "epoch 134, loss 10.811966\n",
      "epoch 135, loss 10.811204\n",
      "epoch 136, loss 10.810442\n",
      "epoch 137, loss 10.809682\n",
      "epoch 138, loss 10.808921\n",
      "epoch 139, loss 10.808161\n",
      "epoch 140, loss 10.807400\n",
      "epoch 141, loss 10.806640\n",
      "epoch 142, loss 10.805881\n",
      "epoch 143, loss 10.805120\n",
      "epoch 144, loss 10.804361\n",
      "epoch 145, loss 10.803602\n",
      "epoch 146, loss 10.802843\n",
      "epoch 147, loss 10.802086\n",
      "epoch 148, loss 10.801328\n",
      "epoch 149, loss 10.800570\n",
      "epoch 150, loss 10.799812\n",
      "epoch 151, loss 10.799055\n",
      "epoch 152, loss 10.798297\n",
      "epoch 153, loss 10.797541\n",
      "epoch 154, loss 10.796784\n",
      "epoch 155, loss 10.796028\n",
      "epoch 156, loss 10.795272\n",
      "epoch 157, loss 10.794516\n",
      "epoch 158, loss 10.793761\n",
      "epoch 159, loss 10.793005\n",
      "epoch 160, loss 10.792251\n",
      "epoch 161, loss 10.791494\n",
      "epoch 162, loss 10.790741\n",
      "epoch 163, loss 10.789988\n",
      "epoch 164, loss 10.789233\n",
      "epoch 165, loss 10.788480\n",
      "epoch 166, loss 10.787725\n",
      "epoch 167, loss 10.786973\n",
      "epoch 168, loss 10.786221\n",
      "epoch 169, loss 10.785467\n",
      "epoch 170, loss 10.784716\n",
      "epoch 171, loss 10.783963\n",
      "epoch 172, loss 10.783212\n",
      "epoch 173, loss 10.782460\n",
      "epoch 174, loss 10.781709\n",
      "epoch 175, loss 10.780958\n",
      "epoch 176, loss 10.780207\n",
      "epoch 177, loss 10.779456\n",
      "epoch 178, loss 10.778707\n",
      "epoch 179, loss 10.777956\n",
      "epoch 180, loss 10.777206\n",
      "epoch 181, loss 10.776457\n",
      "epoch 182, loss 10.775708\n",
      "epoch 183, loss 10.774960\n",
      "epoch 184, loss 10.774211\n",
      "epoch 185, loss 10.773462\n",
      "epoch 186, loss 10.772715\n",
      "epoch 187, loss 10.771967\n",
      "epoch 188, loss 10.771219\n",
      "epoch 189, loss 10.770472\n",
      "epoch 190, loss 10.769724\n",
      "epoch 191, loss 10.768977\n",
      "epoch 192, loss 10.768231\n",
      "epoch 193, loss 10.767485\n",
      "epoch 194, loss 10.766739\n",
      "epoch 195, loss 10.765993\n",
      "epoch 196, loss 10.765247\n",
      "epoch 197, loss 10.764503\n",
      "epoch 198, loss 10.763758\n",
      "epoch 199, loss 10.763013\n",
      "epoch 200, loss 10.762269\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.8300084]\n",
      " [0.5436205]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.09179567]\n",
      "<NDArray 1 @cpu(0)>\n",
      "5\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[ 9.23 10.29]\n",
      " [ 9.24 11.29]\n",
      " [ 9.27 10.44]\n",
      " [ 9.24 10.59]\n",
      " [ 9.2  10.14]\n",
      " [ 9.19 10.14]\n",
      " [ 9.29 10.14]\n",
      " [ 9.26 11.14]\n",
      " [ 9.3  11.44]\n",
      " [ 9.19 11.29]\n",
      " [ 9.24 11.14]\n",
      " [ 9.25 10.14]\n",
      " [ 9.26 10.29]\n",
      " [ 9.3  10.59]\n",
      " [ 9.3  10.29]\n",
      " [ 9.2  11.14]\n",
      " [ 9.25 11.44]\n",
      " [ 9.25 10.59]\n",
      " [ 9.28 10.14]\n",
      " [ 9.24 11.44]\n",
      " [ 9.19 11.14]\n",
      " [ 9.2  10.44]\n",
      " [ 9.23 10.44]\n",
      " [ 9.27 10.14]\n",
      " [ 9.28 10.44]\n",
      " [ 9.24 10.29]\n",
      " [ 9.27 10.59]\n",
      " [ 9.26 11.44]\n",
      " [ 9.28 11.14]\n",
      " [ 9.23 10.14]\n",
      " [ 9.2  11.29]\n",
      " [ 9.28 11.29]\n",
      " [ 9.2  10.29]\n",
      " [ 9.2  11.59]\n",
      " [ 9.29 10.59]\n",
      " [ 9.24 10.44]\n",
      " [ 9.25 10.44]\n",
      " [ 9.25 11.14]\n",
      " [ 9.23 11.29]\n",
      " [ 9.3  11.59]\n",
      " [ 9.19 10.29]\n",
      " [ 9.26 10.59]\n",
      " [ 9.26 10.44]\n",
      " [ 9.23 11.44]\n",
      " [ 9.28 10.29]\n",
      " [ 9.3  11.14]\n",
      " [ 9.27 11.29]\n",
      " [ 9.23 11.59]\n",
      " [ 9.29 11.59]\n",
      " [ 9.25 10.29]\n",
      " [ 9.23 10.59]\n",
      " [ 9.26 10.14]\n",
      " [ 9.29 11.14]\n",
      " [ 9.28 11.59]\n",
      " [ 9.19 10.44]\n",
      " [ 9.19 11.59]\n",
      " [ 9.2  11.44]\n",
      " [ 9.2  10.59]\n",
      " [ 9.28 11.44]\n",
      " [ 9.3  11.29]\n",
      " [ 9.3  10.44]\n",
      " [ 9.29 11.29]\n",
      " [ 9.25 11.29]\n",
      " [ 9.23 11.14]\n",
      " [ 9.27 10.29]\n",
      " [ 9.29 10.44]\n",
      " [ 9.25 11.59]\n",
      " [ 9.24 10.14]\n",
      " [ 9.27 11.14]\n",
      " [ 9.29 10.29]\n",
      " [ 9.27 11.44]\n",
      " [ 9.3  10.14]\n",
      " [ 9.19 10.59]\n",
      " [ 9.28 10.59]\n",
      " [ 9.29 11.44]\n",
      " [ 9.24 11.59]\n",
      " [ 9.26 11.59]\n",
      " [ 9.26 11.29]\n",
      " [ 9.19 11.44]\n",
      " [ 9.27 11.59]]\n",
      "<NDArray 80x2 @cpu(0)> \n",
      "[[ 8.65]\n",
      " [13.73]\n",
      " [11.6 ]\n",
      " [ 8.78]\n",
      " [ 9.81]\n",
      " [15.53]\n",
      " [20.  ]\n",
      " [12.77]\n",
      " [13.05]\n",
      " [14.21]\n",
      " [10.01]\n",
      " [ 7.5 ]\n",
      " [13.37]\n",
      " [12.15]\n",
      " [ 8.64]\n",
      " [10.56]\n",
      " [11.9 ]\n",
      " [ 8.62]\n",
      " [ 9.28]\n",
      " [10.36]\n",
      " [14.08]\n",
      " [10.74]\n",
      " [ 7.91]\n",
      " [ 9.16]\n",
      " [ 5.77]\n",
      " [ 7.65]\n",
      " [11.3 ]\n",
      " [13.12]\n",
      " [10.07]\n",
      " [ 8.95]\n",
      " [12.37]\n",
      " [11.99]\n",
      " [ 8.71]\n",
      " [21.93]\n",
      " [ 8.65]\n",
      " [ 8.62]\n",
      " [12.1 ]\n",
      " [11.31]\n",
      " [14.56]\n",
      " [12.14]\n",
      " [15.45]\n",
      " [10.29]\n",
      " [ 9.33]\n",
      " [11.02]\n",
      " [20.08]\n",
      " [10.89]\n",
      " [10.94]\n",
      " [12.12]\n",
      " [12.22]\n",
      " [ 7.94]\n",
      " [ 8.63]\n",
      " [12.47]\n",
      " [12.21]\n",
      " [10.76]\n",
      " [13.43]\n",
      " [15.91]\n",
      " [10.77]\n",
      " [11.  ]\n",
      " [11.6 ]\n",
      " [25.5 ]\n",
      " [10.35]\n",
      " [ 9.89]\n",
      " [10.01]\n",
      " [ 9.69]\n",
      " [10.32]\n",
      " [11.08]\n",
      " [11.39]\n",
      " [ 8.22]\n",
      " [11.43]\n",
      " [ 5.17]\n",
      " [11.09]\n",
      " [ 9.18]\n",
      " [13.51]\n",
      " [ 9.6 ]\n",
      " [12.77]\n",
      " [14.84]\n",
      " [14.52]\n",
      " [16.69]\n",
      " [13.77]\n",
      " [12.28]]\n",
      "<NDArray 80x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 44.014687\n",
      "epoch 2, loss 27.241858\n",
      "epoch 3, loss 17.699829\n",
      "epoch 4, loss 12.271369\n",
      "epoch 5, loss 9.183101\n",
      "epoch 6, loss 7.426158\n",
      "epoch 7, loss 6.426599\n",
      "epoch 8, loss 5.857912\n",
      "epoch 9, loss 5.534347\n",
      "epoch 10, loss 5.350230\n",
      "epoch 11, loss 5.245445\n",
      "epoch 12, loss 5.185792\n",
      "epoch 13, loss 5.151814\n",
      "epoch 14, loss 5.132442\n",
      "epoch 15, loss 5.121380\n",
      "epoch 16, loss 5.115045\n",
      "epoch 17, loss 5.111400\n",
      "epoch 18, loss 5.109284\n",
      "epoch 19, loss 5.108039\n",
      "epoch 20, loss 5.107289\n",
      "epoch 21, loss 5.106822\n",
      "epoch 22, loss 5.106514\n",
      "epoch 23, loss 5.106297\n",
      "epoch 24, loss 5.106132\n",
      "epoch 25, loss 5.105997\n",
      "epoch 26, loss 5.105878\n",
      "epoch 27, loss 5.105769\n",
      "epoch 28, loss 5.105666\n",
      "epoch 29, loss 5.105566\n",
      "epoch 30, loss 5.105467\n",
      "epoch 31, loss 5.105370\n",
      "epoch 32, loss 5.105273\n",
      "epoch 33, loss 5.105176\n",
      "epoch 34, loss 5.105081\n",
      "epoch 35, loss 5.104984\n",
      "epoch 36, loss 5.104888\n",
      "epoch 37, loss 5.104791\n",
      "epoch 38, loss 5.104696\n",
      "epoch 39, loss 5.104600\n",
      "epoch 40, loss 5.104504\n",
      "epoch 41, loss 5.104408\n",
      "epoch 42, loss 5.104312\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 43, loss 5.104217\n",
      "epoch 44, loss 5.104120\n",
      "epoch 45, loss 5.104024\n",
      "epoch 46, loss 5.103929\n",
      "epoch 47, loss 5.103833\n",
      "epoch 48, loss 5.103738\n",
      "epoch 49, loss 5.103642\n",
      "epoch 50, loss 5.103546\n",
      "epoch 51, loss 5.103450\n",
      "epoch 52, loss 5.103355\n",
      "epoch 53, loss 5.103260\n",
      "epoch 54, loss 5.103164\n",
      "epoch 55, loss 5.103068\n",
      "epoch 56, loss 5.102973\n",
      "epoch 57, loss 5.102878\n",
      "epoch 58, loss 5.102782\n",
      "epoch 59, loss 5.102686\n",
      "epoch 60, loss 5.102592\n",
      "epoch 61, loss 5.102496\n",
      "epoch 62, loss 5.102400\n",
      "epoch 63, loss 5.102305\n",
      "epoch 64, loss 5.102210\n",
      "epoch 65, loss 5.102115\n",
      "epoch 66, loss 5.102019\n",
      "epoch 67, loss 5.101924\n",
      "epoch 68, loss 5.101829\n",
      "epoch 69, loss 5.101734\n",
      "epoch 70, loss 5.101638\n",
      "epoch 71, loss 5.101543\n",
      "epoch 72, loss 5.101449\n",
      "epoch 73, loss 5.101354\n",
      "epoch 74, loss 5.101258\n",
      "epoch 75, loss 5.101164\n",
      "epoch 76, loss 5.101069\n",
      "epoch 77, loss 5.100974\n",
      "epoch 78, loss 5.100879\n",
      "epoch 79, loss 5.100784\n",
      "epoch 80, loss 5.100689\n",
      "epoch 81, loss 5.100595\n",
      "epoch 82, loss 5.100500\n",
      "epoch 83, loss 5.100405\n",
      "epoch 84, loss 5.100310\n",
      "epoch 85, loss 5.100215\n",
      "epoch 86, loss 5.100121\n",
      "epoch 87, loss 5.100026\n",
      "epoch 88, loss 5.099931\n",
      "epoch 89, loss 5.099837\n",
      "epoch 90, loss 5.099742\n",
      "epoch 91, loss 5.099648\n",
      "epoch 92, loss 5.099554\n",
      "epoch 93, loss 5.099460\n",
      "epoch 94, loss 5.099364\n",
      "epoch 95, loss 5.099270\n",
      "epoch 96, loss 5.099175\n",
      "epoch 97, loss 5.099082\n",
      "epoch 98, loss 5.098987\n",
      "epoch 99, loss 5.098893\n",
      "epoch 100, loss 5.098798\n",
      "epoch 101, loss 5.098704\n",
      "epoch 102, loss 5.098610\n",
      "epoch 103, loss 5.098516\n",
      "epoch 104, loss 5.098421\n",
      "epoch 105, loss 5.098327\n",
      "epoch 106, loss 5.098233\n",
      "epoch 107, loss 5.098139\n",
      "epoch 108, loss 5.098045\n",
      "epoch 109, loss 5.097951\n",
      "epoch 110, loss 5.097857\n",
      "epoch 111, loss 5.097763\n",
      "epoch 112, loss 5.097669\n",
      "epoch 113, loss 5.097575\n",
      "epoch 114, loss 5.097481\n",
      "epoch 115, loss 5.097387\n",
      "epoch 116, loss 5.097293\n",
      "epoch 117, loss 5.097199\n",
      "epoch 118, loss 5.097106\n",
      "epoch 119, loss 5.097012\n",
      "epoch 120, loss 5.096918\n",
      "epoch 121, loss 5.096824\n",
      "epoch 122, loss 5.096731\n",
      "epoch 123, loss 5.096637\n",
      "epoch 124, loss 5.096543\n",
      "epoch 125, loss 5.096449\n",
      "epoch 126, loss 5.096356\n",
      "epoch 127, loss 5.096262\n",
      "epoch 128, loss 5.096169\n",
      "epoch 129, loss 5.096075\n",
      "epoch 130, loss 5.095982\n",
      "epoch 131, loss 5.095888\n",
      "epoch 132, loss 5.095795\n",
      "epoch 133, loss 5.095702\n",
      "epoch 134, loss 5.095608\n",
      "epoch 135, loss 5.095515\n",
      "epoch 136, loss 5.095422\n",
      "epoch 137, loss 5.095328\n",
      "epoch 138, loss 5.095235\n",
      "epoch 139, loss 5.095141\n",
      "epoch 140, loss 5.095048\n",
      "epoch 141, loss 5.094955\n",
      "epoch 142, loss 5.094862\n",
      "epoch 143, loss 5.094769\n",
      "epoch 144, loss 5.094676\n",
      "epoch 145, loss 5.094583\n",
      "epoch 146, loss 5.094490\n",
      "epoch 147, loss 5.094397\n",
      "epoch 148, loss 5.094304\n",
      "epoch 149, loss 5.094211\n",
      "epoch 150, loss 5.094117\n",
      "epoch 151, loss 5.094024\n",
      "epoch 152, loss 5.093932\n",
      "epoch 153, loss 5.093839\n",
      "epoch 154, loss 5.093746\n",
      "epoch 155, loss 5.093653\n",
      "epoch 156, loss 5.093560\n",
      "epoch 157, loss 5.093468\n",
      "epoch 158, loss 5.093375\n",
      "epoch 159, loss 5.093282\n",
      "epoch 160, loss 5.093189\n",
      "epoch 161, loss 5.093097\n",
      "epoch 162, loss 5.093004\n",
      "epoch 163, loss 5.092911\n",
      "epoch 164, loss 5.092819\n",
      "epoch 165, loss 5.092726\n",
      "epoch 166, loss 5.092633\n",
      "epoch 167, loss 5.092541\n",
      "epoch 168, loss 5.092448\n",
      "epoch 169, loss 5.092356\n",
      "epoch 170, loss 5.092264\n",
      "epoch 171, loss 5.092171\n",
      "epoch 172, loss 5.092079\n",
      "epoch 173, loss 5.091987\n",
      "epoch 174, loss 5.091894\n",
      "epoch 175, loss 5.091802\n",
      "epoch 176, loss 5.091710\n",
      "epoch 177, loss 5.091618\n",
      "epoch 178, loss 5.091525\n",
      "epoch 179, loss 5.091433\n",
      "epoch 180, loss 5.091340\n",
      "epoch 181, loss 5.091249\n",
      "epoch 182, loss 5.091157\n",
      "epoch 183, loss 5.091064\n",
      "epoch 184, loss 5.090972\n",
      "epoch 185, loss 5.090880\n",
      "epoch 186, loss 5.090788\n",
      "epoch 187, loss 5.090696\n",
      "epoch 188, loss 5.090604\n",
      "epoch 189, loss 5.090512\n",
      "epoch 190, loss 5.090421\n",
      "epoch 191, loss 5.090329\n",
      "epoch 192, loss 5.090236\n",
      "epoch 193, loss 5.090145\n",
      "epoch 194, loss 5.090053\n",
      "epoch 195, loss 5.089961\n",
      "epoch 196, loss 5.089869\n",
      "epoch 197, loss 5.089777\n",
      "epoch 198, loss 5.089686\n",
      "epoch 199, loss 5.089594\n",
      "epoch 200, loss 5.089503\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.48264992]\n",
      " [0.6561943 ]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.05189336]\n",
      "<NDArray 1 @cpu(0)>\n",
      "6\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[ 9.24 13.29]\n",
      " [ 9.29 13.14]\n",
      " [ 9.23 12.29]\n",
      " [ 9.26 12.29]\n",
      " [ 9.29 13.29]\n",
      " [ 9.2  12.59]\n",
      " [ 9.28 13.29]\n",
      " [ 9.3  12.44]\n",
      " [ 9.23 13.59]\n",
      " [ 9.27 12.29]\n",
      " [ 9.3  12.14]\n",
      " [ 9.19 12.44]\n",
      " [ 9.27 13.59]\n",
      " [ 9.23 12.44]\n",
      " [ 9.28 12.59]\n",
      " [ 9.29 12.59]\n",
      " [ 9.23 13.29]\n",
      " [ 9.28 12.44]\n",
      " [ 9.25 12.59]\n",
      " [ 9.28 13.59]\n",
      " [ 9.19 12.29]\n",
      " [ 9.25 13.29]\n",
      " [ 9.27 13.29]\n",
      " [ 9.25 13.59]\n",
      " [ 9.2  13.29]\n",
      " [ 9.29 12.29]\n",
      " [ 9.27 13.14]\n",
      " [ 9.24 12.59]\n",
      " [ 9.25 12.44]\n",
      " [ 9.19 12.14]\n",
      " [ 9.24 12.14]\n",
      " [ 9.27 12.59]\n",
      " [ 9.26 12.44]\n",
      " [ 9.29 12.14]\n",
      " [ 9.3  13.44]\n",
      " [ 9.3  13.59]\n",
      " [ 9.26 12.59]\n",
      " [ 9.2  13.14]\n",
      " [ 9.26 13.14]\n",
      " [ 9.25 13.44]\n",
      " [ 9.23 12.14]\n",
      " [ 9.26 13.44]\n",
      " [ 9.27 12.14]\n",
      " [ 9.19 13.44]\n",
      " [ 9.19 12.59]\n",
      " [ 9.28 13.44]\n",
      " [ 9.26 13.59]\n",
      " [ 9.24 13.44]\n",
      " [ 9.25 12.14]\n",
      " [ 9.2  12.14]\n",
      " [ 9.2  12.29]\n",
      " [ 9.19 13.59]\n",
      " [ 9.24 12.29]\n",
      " [ 9.3  12.59]\n",
      " [ 9.29 13.44]\n",
      " [ 9.3  12.29]\n",
      " [ 9.19 13.29]\n",
      " [ 9.3  13.29]\n",
      " [ 9.28 13.14]\n",
      " [ 9.24 12.44]\n",
      " [ 9.24 13.59]\n",
      " [ 9.23 13.44]\n",
      " [ 9.23 12.59]\n",
      " [ 9.2  13.44]\n",
      " [ 9.28 12.14]\n",
      " [ 9.28 12.29]\n",
      " [ 9.27 12.44]\n",
      " [ 9.26 12.14]\n",
      " [ 9.29 12.44]\n",
      " [ 9.24 13.14]\n",
      " [ 9.2  12.44]\n",
      " [ 9.29 13.59]\n",
      " [ 9.27 13.44]\n",
      " [ 9.26 13.29]\n",
      " [ 9.25 12.29]\n",
      " [ 9.25 13.14]\n",
      " [ 9.19 13.14]\n",
      " [ 9.2  13.59]\n",
      " [ 9.3  13.14]\n",
      " [ 9.23 13.14]]\n",
      "<NDArray 80x2 @cpu(0)> \n",
      "[[ 8.82]\n",
      " [12.55]\n",
      " [13.64]\n",
      " [11.66]\n",
      " [ 9.08]\n",
      " [10.95]\n",
      " [ 8.76]\n",
      " [14.81]\n",
      " [ 8.51]\n",
      " [13.92]\n",
      " [15.29]\n",
      " [13.8 ]\n",
      " [ 7.9 ]\n",
      " [13.52]\n",
      " [12.28]\n",
      " [11.04]\n",
      " [11.02]\n",
      " [13.36]\n",
      " [16.43]\n",
      " [ 8.56]\n",
      " [11.7 ]\n",
      " [13.67]\n",
      " [ 8.69]\n",
      " [ 6.8 ]\n",
      " [12.42]\n",
      " [11.23]\n",
      " [10.14]\n",
      " [10.54]\n",
      " [12.72]\n",
      " [13.68]\n",
      " [24.67]\n",
      " [12.53]\n",
      " [13.25]\n",
      " [12.27]\n",
      " [11.92]\n",
      " [ 9.94]\n",
      " [11.74]\n",
      " [13.54]\n",
      " [12.91]\n",
      " [ 9.79]\n",
      " [15.03]\n",
      " [10.55]\n",
      " [13.61]\n",
      " [ 9.24]\n",
      " [12.96]\n",
      " [10.38]\n",
      " [ 9.53]\n",
      " [ 8.34]\n",
      " [15.27]\n",
      " [24.02]\n",
      " [11.16]\n",
      " [12.01]\n",
      " [25.16]\n",
      " [13.01]\n",
      " [ 9.6 ]\n",
      " [12.96]\n",
      " [11.42]\n",
      " [11.09]\n",
      " [13.89]\n",
      " [13.21]\n",
      " [ 8.55]\n",
      " [ 9.63]\n",
      " [13.77]\n",
      " [ 9.23]\n",
      " [12.47]\n",
      " [14.04]\n",
      " [12.28]\n",
      " [11.13]\n",
      " [12.27]\n",
      " [ 8.96]\n",
      " [11.89]\n",
      " [ 8.98]\n",
      " [ 6.47]\n",
      " [12.19]\n",
      " [13.12]\n",
      " [12.56]\n",
      " [13.1 ]\n",
      " [10.61]\n",
      " [14.63]\n",
      " [12.51]]\n",
      "<NDArray 80x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 41.687218\n",
      "epoch 2, loss 23.294514\n",
      "epoch 3, loss 14.351860\n",
      "epoch 4, loss 10.003734\n",
      "epoch 5, loss 7.889415\n",
      "epoch 6, loss 6.861154\n",
      "epoch 7, loss 6.360925\n",
      "epoch 8, loss 6.117417\n",
      "epoch 9, loss 5.998725\n",
      "epoch 10, loss 5.940718\n",
      "epoch 11, loss 5.912215\n",
      "epoch 12, loss 5.898057\n",
      "epoch 13, loss 5.890873\n",
      "epoch 14, loss 5.887080\n",
      "epoch 15, loss 5.884936\n",
      "epoch 16, loss 5.883594\n",
      "epoch 17, loss 5.882640\n",
      "epoch 18, loss 5.881878\n",
      "epoch 19, loss 5.881207\n",
      "epoch 20, loss 5.880581\n",
      "epoch 21, loss 5.879977\n",
      "epoch 22, loss 5.879383\n",
      "epoch 23, loss 5.878795\n",
      "epoch 24, loss 5.878211\n",
      "epoch 25, loss 5.877626\n",
      "epoch 26, loss 5.877042\n",
      "epoch 27, loss 5.876460\n",
      "epoch 28, loss 5.875876\n",
      "epoch 29, loss 5.875295\n",
      "epoch 30, loss 5.874712\n",
      "epoch 31, loss 5.874131\n",
      "epoch 32, loss 5.873549\n",
      "epoch 33, loss 5.872967\n",
      "epoch 34, loss 5.872384\n",
      "epoch 35, loss 5.871803\n",
      "epoch 36, loss 5.871222\n",
      "epoch 37, loss 5.870641\n",
      "epoch 38, loss 5.870059\n",
      "epoch 39, loss 5.869478\n",
      "epoch 40, loss 5.868898\n",
      "epoch 41, loss 5.868317\n",
      "epoch 42, loss 5.867736\n",
      "epoch 43, loss 5.867156\n",
      "epoch 44, loss 5.866576\n",
      "epoch 45, loss 5.865995\n",
      "epoch 46, loss 5.865415\n",
      "epoch 47, loss 5.864835\n",
      "epoch 48, loss 5.864255\n",
      "epoch 49, loss 5.863676\n",
      "epoch 50, loss 5.863096\n",
      "epoch 51, loss 5.862517\n",
      "epoch 52, loss 5.861938\n",
      "epoch 53, loss 5.861359\n",
      "epoch 54, loss 5.860780\n",
      "epoch 55, loss 5.860200\n",
      "epoch 56, loss 5.859622\n",
      "epoch 57, loss 5.859043\n",
      "epoch 58, loss 5.858465\n",
      "epoch 59, loss 5.857886\n",
      "epoch 60, loss 5.857308\n",
      "epoch 61, loss 5.856730\n",
      "epoch 62, loss 5.856152\n",
      "epoch 63, loss 5.855575\n",
      "epoch 64, loss 5.854997\n",
      "epoch 65, loss 5.854419\n",
      "epoch 66, loss 5.853842\n",
      "epoch 67, loss 5.853265\n",
      "epoch 68, loss 5.852688\n",
      "epoch 69, loss 5.852111\n",
      "epoch 70, loss 5.851534\n",
      "epoch 71, loss 5.850957\n",
      "epoch 72, loss 5.850380\n",
      "epoch 73, loss 5.849804\n",
      "epoch 74, loss 5.849227\n",
      "epoch 75, loss 5.848652\n",
      "epoch 76, loss 5.848075\n",
      "epoch 77, loss 5.847499\n",
      "epoch 78, loss 5.846923\n",
      "epoch 79, loss 5.846347\n",
      "epoch 80, loss 5.845772\n",
      "epoch 81, loss 5.845197\n",
      "epoch 82, loss 5.844622\n",
      "epoch 83, loss 5.844047\n",
      "epoch 84, loss 5.843472\n",
      "epoch 85, loss 5.842896\n",
      "epoch 86, loss 5.842322\n",
      "epoch 87, loss 5.841747\n",
      "epoch 88, loss 5.841173\n",
      "epoch 89, loss 5.840598\n",
      "epoch 90, loss 5.840024\n",
      "epoch 91, loss 5.839450\n",
      "epoch 92, loss 5.838876\n",
      "epoch 93, loss 5.838303\n",
      "epoch 94, loss 5.837729\n",
      "epoch 95, loss 5.837155\n",
      "epoch 96, loss 5.836582\n",
      "epoch 97, loss 5.836009\n",
      "epoch 98, loss 5.835436\n",
      "epoch 99, loss 5.834863\n",
      "epoch 100, loss 5.834290\n",
      "epoch 101, loss 5.833717\n",
      "epoch 102, loss 5.833144\n",
      "epoch 103, loss 5.832572\n",
      "epoch 104, loss 5.832000\n",
      "epoch 105, loss 5.831428\n",
      "epoch 106, loss 5.830855\n",
      "epoch 107, loss 5.830283\n",
      "epoch 108, loss 5.829711\n",
      "epoch 109, loss 5.829140\n",
      "epoch 110, loss 5.828568\n",
      "epoch 111, loss 5.827997\n",
      "epoch 112, loss 5.827425\n",
      "epoch 113, loss 5.826854\n",
      "epoch 114, loss 5.826283\n",
      "epoch 115, loss 5.825713\n",
      "epoch 116, loss 5.825142\n",
      "epoch 117, loss 5.824571\n",
      "epoch 118, loss 5.824000\n",
      "epoch 119, loss 5.823430\n",
      "epoch 120, loss 5.822860\n",
      "epoch 121, loss 5.822289\n",
      "epoch 122, loss 5.821720\n",
      "epoch 123, loss 5.821150\n",
      "epoch 124, loss 5.820580\n",
      "epoch 125, loss 5.820011\n",
      "epoch 126, loss 5.819441\n",
      "epoch 127, loss 5.818871\n",
      "epoch 128, loss 5.818303\n",
      "epoch 129, loss 5.817734\n",
      "epoch 130, loss 5.817165\n",
      "epoch 131, loss 5.816596\n",
      "epoch 132, loss 5.816027\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 133, loss 5.815459\n",
      "epoch 134, loss 5.814890\n",
      "epoch 135, loss 5.814322\n",
      "epoch 136, loss 5.813754\n",
      "epoch 137, loss 5.813186\n",
      "epoch 138, loss 5.812618\n",
      "epoch 139, loss 5.812051\n",
      "epoch 140, loss 5.811482\n",
      "epoch 141, loss 5.810915\n",
      "epoch 142, loss 5.810348\n",
      "epoch 143, loss 5.809781\n",
      "epoch 144, loss 5.809214\n",
      "epoch 145, loss 5.808647\n",
      "epoch 146, loss 5.808080\n",
      "epoch 147, loss 5.807513\n",
      "epoch 148, loss 5.806947\n",
      "epoch 149, loss 5.806380\n",
      "epoch 150, loss 5.805814\n",
      "epoch 151, loss 5.805247\n",
      "epoch 152, loss 5.804682\n",
      "epoch 153, loss 5.804116\n",
      "epoch 154, loss 5.803550\n",
      "epoch 155, loss 5.802983\n",
      "epoch 156, loss 5.802419\n",
      "epoch 157, loss 5.801854\n",
      "epoch 158, loss 5.801288\n",
      "epoch 159, loss 5.800723\n",
      "epoch 160, loss 5.800159\n",
      "epoch 161, loss 5.799593\n",
      "epoch 162, loss 5.799028\n",
      "epoch 163, loss 5.798464\n",
      "epoch 164, loss 5.797899\n",
      "epoch 165, loss 5.797335\n",
      "epoch 166, loss 5.796771\n",
      "epoch 167, loss 5.796207\n",
      "epoch 168, loss 5.795643\n",
      "epoch 169, loss 5.795079\n",
      "epoch 170, loss 5.794515\n",
      "epoch 171, loss 5.793952\n",
      "epoch 172, loss 5.793388\n",
      "epoch 173, loss 5.792825\n",
      "epoch 174, loss 5.792262\n",
      "epoch 175, loss 5.791699\n",
      "epoch 176, loss 5.791136\n",
      "epoch 177, loss 5.790574\n",
      "epoch 178, loss 5.790010\n",
      "epoch 179, loss 5.789448\n",
      "epoch 180, loss 5.788885\n",
      "epoch 181, loss 5.788323\n",
      "epoch 182, loss 5.787761\n",
      "epoch 183, loss 5.787199\n",
      "epoch 184, loss 5.786637\n",
      "epoch 185, loss 5.786076\n",
      "epoch 186, loss 5.785514\n",
      "epoch 187, loss 5.784953\n",
      "epoch 188, loss 5.784391\n",
      "epoch 189, loss 5.783830\n",
      "epoch 190, loss 5.783269\n",
      "epoch 191, loss 5.782708\n",
      "epoch 192, loss 5.782146\n",
      "epoch 193, loss 5.781586\n",
      "epoch 194, loss 5.781026\n",
      "epoch 195, loss 5.780465\n",
      "epoch 196, loss 5.779905\n",
      "epoch 197, loss 5.779345\n",
      "epoch 198, loss 5.778785\n",
      "epoch 199, loss 5.778225\n",
      "epoch 200, loss 5.777665\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.58292  ]\n",
      " [0.5145518]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.06285176]\n",
      "<NDArray 1 @cpu(0)>\n",
      "7\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[ 9.19 14.59]\n",
      " [ 9.27 14.59]\n",
      " [ 9.27 14.29]\n",
      " [ 9.23 14.44]\n",
      " [ 9.24 15.59]\n",
      " [ 9.2  15.59]\n",
      " [ 9.25 15.44]\n",
      " [ 9.29 14.29]\n",
      " [ 9.24 14.44]\n",
      " [ 9.19 14.44]\n",
      " [ 9.23 15.59]\n",
      " [ 9.25 14.59]\n",
      " [ 9.24 15.29]\n",
      " [ 9.24 15.44]\n",
      " [ 9.25 14.44]\n",
      " [ 9.19 14.29]\n",
      " [ 9.3  15.59]\n",
      " [ 9.28 14.59]\n",
      " [ 9.25 14.29]\n",
      " [ 9.29 15.29]\n",
      " [ 9.26 14.44]\n",
      " [ 9.29 15.59]\n",
      " [ 9.3  15.29]\n",
      " [ 9.26 15.59]\n",
      " [ 9.2  14.59]\n",
      " [ 9.19 15.44]\n",
      " [ 9.27 15.29]\n",
      " [ 9.19 15.29]\n",
      " [ 9.24 15.14]\n",
      " [ 9.19 15.14]\n",
      " [ 9.28 15.29]\n",
      " [ 9.2  14.29]\n",
      " [ 9.26 15.14]\n",
      " [ 9.2  15.14]\n",
      " [ 9.24 14.59]\n",
      " [ 9.3  15.14]\n",
      " [ 9.2  15.44]\n",
      " [ 9.23 14.29]\n",
      " [ 9.26 14.14]\n",
      " [ 9.29 15.44]\n",
      " [ 9.23 14.59]\n",
      " [ 9.19 14.14]\n",
      " [ 9.27 14.14]\n",
      " [ 9.24 14.29]\n",
      " [ 9.23 15.29]\n",
      " [ 9.29 14.44]\n",
      " [ 9.29 14.59]\n",
      " [ 9.25 15.14]\n",
      " [ 9.27 15.14]\n",
      " [ 9.28 15.44]\n",
      " [ 9.27 14.44]\n",
      " [ 9.26 15.44]\n",
      " [ 9.2  14.14]\n",
      " [ 9.3  14.59]\n",
      " [ 9.3  14.44]\n",
      " [ 9.27 15.44]\n",
      " [ 9.26 14.59]\n",
      " [ 9.25 15.59]\n",
      " [ 9.23 15.44]\n",
      " [ 9.19 15.59]\n",
      " [ 9.3  15.44]\n",
      " [ 9.25 15.29]\n",
      " [ 9.2  15.29]\n",
      " [ 9.28 14.44]\n",
      " [ 9.26 14.29]\n",
      " [ 9.23 14.14]\n",
      " [ 9.29 14.14]\n",
      " [ 9.28 15.59]\n",
      " [ 9.24 14.14]\n",
      " [ 9.23 15.14]\n",
      " [ 9.3  14.14]\n",
      " [ 9.27 15.59]\n",
      " [ 9.28 15.14]\n",
      " [ 9.28 14.14]\n",
      " [ 9.25 14.14]\n",
      " [ 9.29 15.14]\n",
      " [ 9.26 15.29]\n",
      " [ 9.28 14.29]\n",
      " [ 9.2  14.44]\n",
      " [ 9.3  14.29]]\n",
      "<NDArray 80x2 @cpu(0)> \n",
      "[[ 9.32]\n",
      " [ 9.59]\n",
      " [10.05]\n",
      " [ 7.74]\n",
      " [ 5.79]\n",
      " [ 8.91]\n",
      " [ 6.92]\n",
      " [10.36]\n",
      " [ 5.77]\n",
      " [ 9.76]\n",
      " [10.41]\n",
      " [ 9.18]\n",
      " [10.5 ]\n",
      " [ 6.05]\n",
      " [ 4.07]\n",
      " [10.76]\n",
      " [10.57]\n",
      " [ 9.51]\n",
      " [21.37]\n",
      " [10.41]\n",
      " [10.76]\n",
      " [ 6.34]\n",
      " [10.89]\n",
      " [ 9.67]\n",
      " [ 7.7 ]\n",
      " [ 9.79]\n",
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      " [ 9.  ]\n",
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      " [ 8.09]\n",
      " [ 8.44]]\n",
      "<NDArray 80x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 21.076408\n",
      "epoch 2, loss 10.558428\n",
      "epoch 3, loss 6.374482\n",
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      "epoch 171, loss 3.592911\n",
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      "epoch 173, loss 3.592700\n",
      "epoch 174, loss 3.592595\n",
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      "epoch 182, loss 3.591752\n",
      "epoch 183, loss 3.591647\n",
      "epoch 184, loss 3.591542\n",
      "epoch 185, loss 3.591436\n",
      "epoch 186, loss 3.591331\n",
      "epoch 187, loss 3.591225\n",
      "epoch 188, loss 3.591120\n",
      "epoch 189, loss 3.591016\n",
      "epoch 190, loss 3.590910\n",
      "epoch 191, loss 3.590805\n",
      "epoch 192, loss 3.590700\n",
      "epoch 193, loss 3.590595\n",
      "epoch 194, loss 3.590490\n",
      "epoch 195, loss 3.590385\n",
      "epoch 196, loss 3.590279\n",
      "epoch 197, loss 3.590175\n",
      "epoch 198, loss 3.590070\n",
      "epoch 199, loss 3.589964\n",
      "epoch 200, loss 3.589860\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.3393034]\n",
      " [0.4085721]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.03704355]\n",
      "<NDArray 1 @cpu(0)>\n",
      "8\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[ 9.29 16.29]\n",
      " [ 9.29 16.59]\n",
      " [ 9.27 15.59]\n",
      " [ 9.3  16.59]\n",
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      " [ 9.26 15.14]]\n",
      "<NDArray 40x2 @cpu(0)> \n",
      "[[ 8.49]\n",
      " [ 8.96]\n",
      " [ 6.87]\n",
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      " [ 9.3 ]\n",
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      " [ 6.56]\n",
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      " [23.3 ]\n",
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      " [10.89]\n",
      " [ 8.47]\n",
      " [ 8.71]\n",
      " [ 7.55]\n",
      " [ 9.65]]\n",
      "<NDArray 40x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 30.834431\n",
      "epoch 2, loss 20.876156\n",
      "epoch 3, loss 14.557138\n",
      "epoch 4, loss 10.547410\n",
      "epoch 5, loss 8.003039\n",
      "epoch 6, loss 6.388510\n",
      "epoch 7, loss 5.364012\n",
      "epoch 8, loss 4.713915\n",
      "epoch 9, loss 4.301396\n",
      "epoch 10, loss 4.039632\n",
      "epoch 11, loss 3.873528\n",
      "epoch 12, loss 3.768127\n",
      "epoch 13, loss 3.701242\n",
      "epoch 14, loss 3.658802\n",
      "epoch 15, loss 3.631869\n",
      "epoch 16, loss 3.614778\n",
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      "epoch 18, loss 3.597049\n",
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      "epoch 20, loss 3.589908\n",
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      "epoch 174, loss 3.584711\n",
      "epoch 175, loss 3.584709\n",
      "epoch 176, loss 3.584707\n",
      "epoch 177, loss 3.584704\n",
      "epoch 178, loss 3.584702\n",
      "epoch 179, loss 3.584699\n",
      "epoch 180, loss 3.584697\n",
      "epoch 181, loss 3.584693\n",
      "epoch 182, loss 3.584692\n",
      "epoch 183, loss 3.584689\n",
      "epoch 184, loss 3.584687\n",
      "epoch 185, loss 3.584684\n",
      "epoch 186, loss 3.584681\n",
      "epoch 187, loss 3.584679\n",
      "epoch 188, loss 3.584677\n",
      "epoch 189, loss 3.584674\n",
      "epoch 190, loss 3.584671\n",
      "epoch 191, loss 3.584669\n",
      "epoch 192, loss 3.584667\n",
      "epoch 193, loss 3.584664\n",
      "epoch 194, loss 3.584662\n",
      "epoch 195, loss 3.584660\n",
      "epoch 196, loss 3.584657\n",
      "epoch 197, loss 3.584654\n",
      "epoch 198, loss 3.584651\n",
      "epoch 199, loss 3.584649\n",
      "epoch 200, loss 3.584647\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.25823388]\n",
      " [0.42406097]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.02671223]\n",
      "<NDArray 1 @cpu(0)>\n",
      "9\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[ 9.23 17.14]\n",
      " [ 9.25 18.59]\n",
      " [ 9.27 17.14]\n",
      " [ 9.23 17.44]\n",
      " [ 9.24 17.44]\n",
      " [ 9.3  18.29]\n",
      " [ 9.28 18.59]\n",
      " [ 9.3  17.59]\n",
      " [ 9.25 18.29]\n",
      " [ 9.24 18.14]\n",
      " [ 9.2  17.29]\n",
      " [ 9.28 18.14]\n",
      " [ 9.2  18.44]\n",
      " [ 9.25 17.59]\n",
      " [ 9.3  18.44]\n",
      " [ 9.28 17.14]\n",
      " [ 9.27 18.29]\n",
      " [ 9.29 18.59]\n",
      " [ 9.28 18.44]\n",
      " [ 9.2  18.14]\n",
      " [ 9.3  18.14]\n",
      " [ 9.27 18.14]\n",
      " [ 9.23 18.14]\n",
      " [ 9.2  17.44]\n",
      " [ 9.26 18.59]\n",
      " [ 9.25 18.44]\n",
      " [ 9.3  17.29]\n",
      " [ 9.19 17.14]\n",
      " [ 9.19 18.59]\n",
      " [ 9.3  17.14]\n",
      " [ 9.29 17.14]\n",
      " [ 9.19 18.44]\n",
      " [ 9.24 17.59]\n",
      " [ 9.29 18.29]\n",
      " [ 9.19 18.29]\n",
      " [ 9.2  17.14]\n",
      " [ 9.25 17.29]\n",
      " [ 9.25 17.14]\n",
      " [ 9.28 17.59]\n",
      " [ 9.19 17.44]\n",
      " [ 9.24 17.29]\n",
      " [ 9.23 18.44]\n",
      " [ 9.26 17.59]\n",
      " [ 9.2  17.59]\n",
      " [ 9.24 17.14]\n",
      " [ 9.26 18.29]\n",
      " [ 9.28 18.29]\n",
      " [ 9.27 18.44]\n",
      " [ 9.27 17.29]\n",
      " [ 9.29 18.44]\n",
      " [ 9.29 17.59]\n",
      " [ 9.19 18.14]\n",
      " [ 9.27 17.59]\n",
      " [ 9.25 18.14]\n",
      " [ 9.26 18.14]\n",
      " [ 9.25 17.44]\n",
      " [ 9.23 18.59]\n",
      " [ 9.26 17.44]\n",
      " [ 9.26 18.44]\n",
      " [ 9.28 17.29]\n",
      " [ 9.26 17.29]\n",
      " [ 9.23 17.29]\n",
      " [ 9.29 17.44]\n",
      " [ 9.23 17.59]\n",
      " [ 9.26 17.14]\n",
      " [ 9.24 18.44]\n",
      " [ 9.19 17.29]\n",
      " [ 9.3  17.44]\n",
      " [ 9.3  18.59]\n",
      " [ 9.2  18.59]\n",
      " [ 9.23 18.29]\n",
      " [ 9.2  18.29]\n",
      " [ 9.19 17.59]\n",
      " [ 9.29 17.29]\n",
      " [ 9.24 18.29]\n",
      " [ 9.29 18.14]\n",
      " [ 9.27 18.59]\n",
      " [ 9.28 17.44]\n",
      " [ 9.27 17.44]\n",
      " [ 9.24 18.59]]\n",
      "<NDArray 80x2 @cpu(0)> \n",
      "[[ 8.71]\n",
      " [ 9.01]\n",
      " [ 8.77]\n",
      " [ 8.05]\n",
      " [ 8.05]\n",
      " [10.86]\n",
      " [11.14]\n",
      " [ 7.95]\n",
      " [10.3 ]\n",
      " [ 7.48]\n",
      " [ 9.41]\n",
      " [ 9.44]\n",
      " [11.86]\n",
      " [ 7.79]\n",
      " [10.04]\n",
      " [ 8.6 ]\n",
      " [12.76]\n",
      " [14.22]\n",
      " [10.37]\n",
      " [10.55]\n",
      " [ 8.87]\n",
      " [11.57]\n",
      " [ 9.72]\n",
      " [10.02]\n",
      " [13.67]\n",
      " [11.07]\n",
      " [10.1 ]\n",
      " [ 9.9 ]\n",
      " [11.59]\n",
      " [10.16]\n",
      " [ 8.31]\n",
      " [13.27]\n",
      " [10.72]\n",
      " [14.27]\n",
      " [12.74]\n",
      " [ 9.48]\n",
      " [ 8.35]\n",
      " [10.64]\n",
      " [ 8.85]\n",
      " [13.33]\n",
      " [ 6.77]\n",
      " [11.06]\n",
      " [16.96]\n",
      " [10.93]\n",
      " [ 8.41]\n",
      " [11.5 ]\n",
      " [24.21]\n",
      " [23.52]\n",
      " [ 9.12]\n",
      " [11.47]\n",
      " [ 9.48]\n",
      " [11.87]\n",
      " [10.29]\n",
      " [ 9.04]\n",
      " [12.58]\n",
      " [ 7.89]\n",
      " [10.25]\n",
      " [11.72]\n",
      " [11.71]\n",
      " [ 9.41]\n",
      " [11.13]\n",
      " [ 6.72]\n",
      " [10.15]\n",
      " [ 6.65]\n",
      " [ 9.36]\n",
      " [11.26]\n",
      " [12.67]\n",
      " [ 9.68]\n",
      " [11.63]\n",
      " [12.58]\n",
      " [13.34]\n",
      " [10.32]\n",
      " [13.14]\n",
      " [ 8.9 ]\n",
      " [ 9.18]\n",
      " [11.42]\n",
      " [20.19]\n",
      " [ 8.51]\n",
      " [ 8.84]\n",
      " [14.72]]\n",
      "<NDArray 80x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 19.905519\n",
      "epoch 2, loss 8.444151\n",
      "epoch 3, loss 5.429565\n",
      "epoch 4, loss 4.636612\n",
      "epoch 5, loss 4.427982\n",
      "epoch 6, loss 4.373038\n",
      "epoch 7, loss 4.358515\n",
      "epoch 8, loss 4.354624\n",
      "epoch 9, loss 4.353529\n",
      "epoch 10, loss 4.353169\n",
      "epoch 11, loss 4.353004\n",
      "epoch 12, loss 4.352889\n",
      "epoch 13, loss 4.352787\n",
      "epoch 14, loss 4.352689\n",
      "epoch 15, loss 4.352592\n",
      "epoch 16, loss 4.352494\n",
      "epoch 17, loss 4.352397\n",
      "epoch 18, loss 4.352301\n",
      "epoch 19, loss 4.352204\n",
      "epoch 20, loss 4.352107\n",
      "epoch 21, loss 4.352010\n",
      "epoch 22, loss 4.351913\n",
      "epoch 23, loss 4.351817\n",
      "epoch 24, loss 4.351720\n",
      "epoch 25, loss 4.351624\n",
      "epoch 26, loss 4.351527\n",
      "epoch 27, loss 4.351430\n",
      "epoch 28, loss 4.351333\n",
      "epoch 29, loss 4.351237\n",
      "epoch 30, loss 4.351140\n",
      "epoch 31, loss 4.351043\n",
      "epoch 32, loss 4.350946\n",
      "epoch 33, loss 4.350850\n",
      "epoch 34, loss 4.350753\n",
      "epoch 35, loss 4.350657\n",
      "epoch 36, loss 4.350560\n",
      "epoch 37, loss 4.350463\n",
      "epoch 38, loss 4.350367\n",
      "epoch 39, loss 4.350270\n",
      "epoch 40, loss 4.350173\n",
      "epoch 41, loss 4.350077\n",
      "epoch 42, loss 4.349981\n",
      "epoch 43, loss 4.349885\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 44, loss 4.349788\n",
      "epoch 45, loss 4.349691\n",
      "epoch 46, loss 4.349595\n",
      "epoch 47, loss 4.349499\n",
      "epoch 48, loss 4.349402\n",
      "epoch 49, loss 4.349306\n",
      "epoch 50, loss 4.349209\n",
      "epoch 51, loss 4.349113\n",
      "epoch 52, loss 4.349016\n",
      "epoch 53, loss 4.348920\n",
      "epoch 54, loss 4.348824\n",
      "epoch 55, loss 4.348727\n",
      "epoch 56, loss 4.348631\n",
      "epoch 57, loss 4.348535\n",
      "epoch 58, loss 4.348439\n",
      "epoch 59, loss 4.348342\n",
      "epoch 60, loss 4.348246\n",
      "epoch 61, loss 4.348150\n",
      "epoch 62, loss 4.348054\n",
      "epoch 63, loss 4.347957\n",
      "epoch 64, loss 4.347861\n",
      "epoch 65, loss 4.347764\n",
      "epoch 66, loss 4.347669\n",
      "epoch 67, loss 4.347572\n",
      "epoch 68, loss 4.347476\n",
      "epoch 69, loss 4.347381\n",
      "epoch 70, loss 4.347284\n",
      "epoch 71, loss 4.347188\n",
      "epoch 72, loss 4.347092\n",
      "epoch 73, loss 4.346996\n",
      "epoch 74, loss 4.346900\n",
      "epoch 75, loss 4.346805\n",
      "epoch 76, loss 4.346708\n",
      "epoch 77, loss 4.346612\n",
      "epoch 78, loss 4.346515\n",
      "epoch 79, loss 4.346420\n",
      "epoch 80, loss 4.346324\n",
      "epoch 81, loss 4.346228\n",
      "epoch 82, loss 4.346132\n",
      "epoch 83, loss 4.346036\n",
      "epoch 84, loss 4.345940\n",
      "epoch 85, loss 4.345844\n",
      "epoch 86, loss 4.345748\n",
      "epoch 87, loss 4.345653\n",
      "epoch 88, loss 4.345556\n",
      "epoch 89, loss 4.345460\n",
      "epoch 90, loss 4.345365\n",
      "epoch 91, loss 4.345269\n",
      "epoch 92, loss 4.345173\n",
      "epoch 93, loss 4.345078\n",
      "epoch 94, loss 4.344982\n",
      "epoch 95, loss 4.344886\n",
      "epoch 96, loss 4.344790\n",
      "epoch 97, loss 4.344694\n",
      "epoch 98, loss 4.344599\n",
      "epoch 99, loss 4.344502\n",
      "epoch 100, loss 4.344407\n",
      "epoch 101, loss 4.344312\n",
      "epoch 102, loss 4.344215\n",
      "epoch 103, loss 4.344120\n",
      "epoch 104, loss 4.344024\n",
      "epoch 105, loss 4.343929\n",
      "epoch 106, loss 4.343833\n",
      "epoch 107, loss 4.343738\n",
      "epoch 108, loss 4.343642\n",
      "epoch 109, loss 4.343547\n",
      "epoch 110, loss 4.343451\n",
      "epoch 111, loss 4.343355\n",
      "epoch 112, loss 4.343259\n",
      "epoch 113, loss 4.343164\n",
      "epoch 114, loss 4.343068\n",
      "epoch 115, loss 4.342973\n",
      "epoch 116, loss 4.342877\n",
      "epoch 117, loss 4.342782\n",
      "epoch 118, loss 4.342687\n",
      "epoch 119, loss 4.342591\n",
      "epoch 120, loss 4.342496\n",
      "epoch 121, loss 4.342401\n",
      "epoch 122, loss 4.342305\n",
      "epoch 123, loss 4.342210\n",
      "epoch 124, loss 4.342114\n",
      "epoch 125, loss 4.342019\n",
      "epoch 126, loss 4.341923\n",
      "epoch 127, loss 4.341828\n",
      "epoch 128, loss 4.341733\n",
      "epoch 129, loss 4.341638\n",
      "epoch 130, loss 4.341542\n",
      "epoch 131, loss 4.341447\n",
      "epoch 132, loss 4.341352\n",
      "epoch 133, loss 4.341257\n",
      "epoch 134, loss 4.341161\n",
      "epoch 135, loss 4.341066\n",
      "epoch 136, loss 4.340971\n",
      "epoch 137, loss 4.340876\n",
      "epoch 138, loss 4.340781\n",
      "epoch 139, loss 4.340686\n",
      "epoch 140, loss 4.340590\n",
      "epoch 141, loss 4.340495\n",
      "epoch 142, loss 4.340400\n",
      "epoch 143, loss 4.340305\n",
      "epoch 144, loss 4.340210\n",
      "epoch 145, loss 4.340115\n",
      "epoch 146, loss 4.340020\n",
      "epoch 147, loss 4.339925\n",
      "epoch 148, loss 4.339829\n",
      "epoch 149, loss 4.339735\n",
      "epoch 150, loss 4.339640\n",
      "epoch 151, loss 4.339545\n",
      "epoch 152, loss 4.339449\n",
      "epoch 153, loss 4.339355\n",
      "epoch 154, loss 4.339260\n",
      "epoch 155, loss 4.339165\n",
      "epoch 156, loss 4.339070\n",
      "epoch 157, loss 4.338975\n",
      "epoch 158, loss 4.338880\n",
      "epoch 159, loss 4.338785\n",
      "epoch 160, loss 4.338690\n",
      "epoch 161, loss 4.338595\n",
      "epoch 162, loss 4.338500\n",
      "epoch 163, loss 4.338406\n",
      "epoch 164, loss 4.338311\n",
      "epoch 165, loss 4.338216\n",
      "epoch 166, loss 4.338121\n",
      "epoch 167, loss 4.338027\n",
      "epoch 168, loss 4.337932\n",
      "epoch 169, loss 4.337837\n",
      "epoch 170, loss 4.337742\n",
      "epoch 171, loss 4.337647\n",
      "epoch 172, loss 4.337553\n",
      "epoch 173, loss 4.337458\n",
      "epoch 174, loss 4.337363\n",
      "epoch 175, loss 4.337268\n",
      "epoch 176, loss 4.337174\n",
      "epoch 177, loss 4.337080\n",
      "epoch 178, loss 4.336985\n",
      "epoch 179, loss 4.336890\n",
      "epoch 180, loss 4.336795\n",
      "epoch 181, loss 4.336701\n",
      "epoch 182, loss 4.336607\n",
      "epoch 183, loss 4.336512\n",
      "epoch 184, loss 4.336417\n",
      "epoch 185, loss 4.336323\n",
      "epoch 186, loss 4.336228\n",
      "epoch 187, loss 4.336133\n",
      "epoch 188, loss 4.336040\n",
      "epoch 189, loss 4.335944\n",
      "epoch 190, loss 4.335851\n",
      "epoch 191, loss 4.335756\n",
      "epoch 192, loss 4.335662\n",
      "epoch 193, loss 4.335567\n",
      "epoch 194, loss 4.335473\n",
      "epoch 195, loss 4.335378\n",
      "epoch 196, loss 4.335284\n",
      "epoch 197, loss 4.335190\n",
      "epoch 198, loss 4.335095\n",
      "epoch 199, loss 4.335001\n",
      "epoch 200, loss 4.334907\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.21087421]\n",
      " [0.5002913 ]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.02032579]\n",
      "<NDArray 1 @cpu(0)>\n",
      "10\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[ 9.26 20.59]\n",
      " [ 9.28 19.59]\n",
      " [ 9.27 19.29]\n",
      " [ 9.25 19.29]\n",
      " [ 9.26 19.14]\n",
      " [ 9.25 20.29]\n",
      " [ 9.26 19.29]\n",
      " [ 9.29 19.29]\n",
      " [ 9.28 19.29]\n",
      " [ 9.22 20.44]\n",
      " [ 9.27 19.44]\n",
      " [ 9.23 19.29]\n",
      " [ 9.27 19.59]\n",
      " [ 9.29 19.59]\n",
      " [ 9.29 19.14]\n",
      " [ 9.24 19.59]\n",
      " [ 9.19 20.44]\n",
      " [ 9.25 19.59]\n",
      " [ 9.29 19.44]\n",
      " [ 9.29 20.59]\n",
      " [ 9.26 20.44]\n",
      " [ 9.3  19.59]\n",
      " [ 9.23 20.14]\n",
      " [ 9.26 20.14]\n",
      " [ 9.28 20.44]\n",
      " [ 9.27 20.59]\n",
      " [ 9.19 19.44]\n",
      " [ 9.25 20.14]\n",
      " [ 9.29 20.29]\n",
      " [ 9.29 20.44]\n",
      " [ 9.24 19.44]\n",
      " [ 9.3  20.14]\n",
      " [ 9.19 19.59]\n",
      " [ 9.27 20.14]\n",
      " [ 9.24 20.29]\n",
      " [ 9.3  20.29]\n",
      " [ 9.19 19.14]\n",
      " [ 9.26 19.59]\n",
      " [ 9.25 19.44]\n",
      " [ 9.27 20.29]\n",
      " [ 9.23 20.59]\n",
      " [ 9.19 19.29]\n",
      " [ 9.23 19.14]\n",
      " [ 9.24 20.14]\n",
      " [ 9.28 20.14]\n",
      " [ 9.3  19.29]\n",
      " [ 9.26 20.29]\n",
      " [ 9.28 19.44]\n",
      " [ 9.25 20.59]\n",
      " [ 9.26 19.44]\n",
      " [ 9.3  20.59]\n",
      " [ 9.28 20.29]\n",
      " [ 9.28 19.14]\n",
      " [ 9.29 20.14]\n",
      " [ 9.23 20.29]\n",
      " [ 9.27 19.14]\n",
      " [ 9.23 19.44]\n",
      " [ 9.19 20.29]\n",
      " [ 9.25 19.14]\n",
      " [ 9.28 20.59]\n",
      " [ 9.23 19.59]\n",
      " [ 9.19 20.59]\n",
      " [ 9.24 20.44]\n",
      " [ 9.24 19.29]\n",
      " [ 9.3  19.14]\n",
      " [ 9.27 20.44]\n",
      " [ 9.23 20.44]\n",
      " [ 9.25 20.44]\n",
      " [ 9.24 19.14]\n",
      " [ 9.24 20.59]\n",
      " [ 9.19 20.14]\n",
      " [ 9.3  19.44]\n",
      " [ 9.3  20.44]\n",
      " [ 9.22 20.59]]\n",
      "<NDArray 74x2 @cpu(0)> \n",
      "[[17.81]\n",
      " [12.04]\n",
      " [13.04]\n",
      " [ 9.55]\n",
      " [11.27]\n",
      " [10.72]\n",
      " [14.38]\n",
      " [23.26]\n",
      " [10.94]\n",
      " [14.57]\n",
      " [ 9.49]\n",
      " [12.66]\n",
      " [10.45]\n",
      " [11.83]\n",
      " [11.21]\n",
      " [ 7.77]\n",
      " [11.26]\n",
      " [ 9.21]\n",
      " [10.13]\n",
      " [13.19]\n",
      " [15.24]\n",
      " [ 9.59]\n",
      " [20.51]\n",
      " [14.45]\n",
      " [11.94]\n",
      " [13.19]\n",
      " [13.51]\n",
      " [10.41]\n",
      " [12.01]\n",
      " [13.28]\n",
      " [22.05]\n",
      " [12.29]\n",
      " [12.19]\n",
      " [11.15]\n",
      " [10.75]\n",
      " [ 9.88]\n",
      " [12.12]\n",
      " [12.98]\n",
      " [11.64]\n",
      " [14.43]\n",
      " [12.73]\n",
      " [12.4 ]\n",
      " [12.51]\n",
      " [10.27]\n",
      " [12.84]\n",
      " [22.39]\n",
      " [13.26]\n",
      " [11.61]\n",
      " [13.94]\n",
      " [13.1 ]\n",
      " [13.2 ]\n",
      " [12.14]\n",
      " [11.56]\n",
      " [12.71]\n",
      " [15.7 ]\n",
      " [12.79]\n",
      " [10.62]\n",
      " [10.02]\n",
      " [11.94]\n",
      " [13.49]\n",
      " [ 9.21]\n",
      " [22.84]\n",
      " [14.02]\n",
      " [10.45]\n",
      " [21.34]\n",
      " [13.31]\n",
      " [13.44]\n",
      " [10.25]\n",
      " [14.47]\n",
      " [11.62]\n",
      " [14.26]\n",
      " [10.72]\n",
      " [12.16]\n",
      " [25.01]]\n",
      "<NDArray 74x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 25.525049\n",
      "epoch 2, loss 10.232290\n",
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      "epoch 126, loss 6.019241\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 127, loss 6.019241\n",
      "epoch 128, loss 6.019240\n",
      "epoch 129, loss 6.019239\n",
      "epoch 130, loss 6.019238\n",
      "epoch 131, loss 6.019237\n",
      "epoch 132, loss 6.019236\n",
      "epoch 133, loss 6.019235\n",
      "epoch 134, loss 6.019234\n",
      "epoch 135, loss 6.019233\n",
      "epoch 136, loss 6.019231\n",
      "epoch 137, loss 6.019231\n",
      "epoch 138, loss 6.019230\n",
      "epoch 139, loss 6.019229\n",
      "epoch 140, loss 6.019228\n",
      "epoch 141, loss 6.019227\n",
      "epoch 142, loss 6.019227\n",
      "epoch 143, loss 6.019225\n",
      "epoch 144, loss 6.019224\n",
      "epoch 145, loss 6.019223\n",
      "epoch 146, loss 6.019222\n",
      "epoch 147, loss 6.019221\n",
      "epoch 148, loss 6.019220\n",
      "epoch 149, loss 6.019219\n",
      "epoch 150, loss 6.019218\n",
      "epoch 151, loss 6.019217\n",
      "epoch 152, loss 6.019216\n",
      "epoch 153, loss 6.019216\n",
      "epoch 154, loss 6.019214\n",
      "epoch 155, loss 6.019213\n",
      "epoch 156, loss 6.019212\n",
      "epoch 157, loss 6.019211\n",
      "epoch 158, loss 6.019210\n",
      "epoch 159, loss 6.019209\n",
      "epoch 160, loss 6.019208\n",
      "epoch 161, loss 6.019207\n",
      "epoch 162, loss 6.019207\n",
      "epoch 163, loss 6.019206\n",
      "epoch 164, loss 6.019204\n",
      "epoch 165, loss 6.019203\n",
      "epoch 166, loss 6.019203\n",
      "epoch 167, loss 6.019201\n",
      "epoch 168, loss 6.019200\n",
      "epoch 169, loss 6.019200\n",
      "epoch 170, loss 6.019198\n",
      "epoch 171, loss 6.019197\n",
      "epoch 172, loss 6.019197\n",
      "epoch 173, loss 6.019196\n",
      "epoch 174, loss 6.019194\n",
      "epoch 175, loss 6.019193\n",
      "epoch 176, loss 6.019193\n",
      "epoch 177, loss 6.019192\n",
      "epoch 178, loss 6.019191\n",
      "epoch 179, loss 6.019189\n",
      "epoch 180, loss 6.019188\n",
      "epoch 181, loss 6.019188\n",
      "epoch 182, loss 6.019187\n",
      "epoch 183, loss 6.019186\n",
      "epoch 184, loss 6.019185\n",
      "epoch 185, loss 6.019184\n",
      "epoch 186, loss 6.019183\n",
      "epoch 187, loss 6.019182\n",
      "epoch 188, loss 6.019181\n",
      "epoch 189, loss 6.019180\n",
      "epoch 190, loss 6.019179\n",
      "epoch 191, loss 6.019178\n",
      "epoch 192, loss 6.019177\n",
      "epoch 193, loss 6.019176\n",
      "epoch 194, loss 6.019175\n",
      "epoch 195, loss 6.019174\n",
      "epoch 196, loss 6.019173\n",
      "epoch 197, loss 6.019172\n",
      "epoch 198, loss 6.019171\n",
      "epoch 199, loss 6.019170\n",
      "epoch 200, loss 6.019169\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.24993859]\n",
      " [0.54213965]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.02738119]\n",
      "<NDArray 1 @cpu(0)>\n",
      "11\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[ 9.19 22.59]\n",
      " [ 9.3  22.29]\n",
      " [ 9.25 21.44]\n",
      " [ 9.28 21.29]\n",
      " [ 9.29 22.29]\n",
      " [ 9.28 22.44]\n",
      " [ 9.23 21.44]\n",
      " [ 9.27 22.14]\n",
      " [ 9.3  22.59]\n",
      " [ 9.22 22.14]\n",
      " [ 9.3  21.14]\n",
      " [ 9.27 22.44]\n",
      " [ 9.3  22.14]\n",
      " [ 9.22 21.29]\n",
      " [ 9.22 21.44]\n",
      " [ 9.27 22.29]\n",
      " [ 9.27 21.14]\n",
      " [ 9.3  21.44]\n",
      " [ 9.19 21.14]\n",
      " [ 9.19 21.59]\n",
      " [ 9.29 21.59]\n",
      " [ 9.24 22.14]\n",
      " [ 9.28 21.44]\n",
      " [ 9.29 21.44]\n",
      " [ 9.28 22.59]\n",
      " [ 9.3  21.59]\n",
      " [ 9.26 22.29]\n",
      " [ 9.24 21.59]\n",
      " [ 9.3  21.29]\n",
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      " [ 9.26 21.29]\n",
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      " [ 9.22 21.59]\n",
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      " [ 9.26 22.44]\n",
      " [ 9.3  22.44]\n",
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      " [ 9.28 21.14]\n",
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      " [ 9.29 22.44]\n",
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      " [ 9.19 22.29]\n",
      " [ 9.19 22.14]\n",
      " [ 9.18 22.59]\n",
      " [ 9.19 22.44]\n",
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      " [ 9.25 22.14]\n",
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      " [ 9.29 21.29]\n",
      " [ 9.26 21.44]\n",
      " [ 9.26 21.59]\n",
      " [ 9.25 22.59]]\n",
      "<NDArray 82x2 @cpu(0)> \n",
      "[[ 8.37]\n",
      " [18.19]\n",
      " [16.17]\n",
      " [14.03]\n",
      " [13.91]\n",
      " [10.64]\n",
      " [13.81]\n",
      " [18.11]\n",
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      " [17.63]\n",
      " [14.4 ]\n",
      " [10.04]\n",
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      " [14.78]\n",
      " [11.66]\n",
      " [10.9 ]\n",
      " [ 8.57]\n",
      " [10.57]\n",
      " [17.49]\n",
      " [ 9.15]\n",
      " [ 9.78]\n",
      " [26.26]\n",
      " [10.01]\n",
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      " [ 9.34]\n",
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      " [10.09]\n",
      " [ 8.28]\n",
      " [ 8.18]\n",
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      " [11.11]\n",
      " [12.36]\n",
      " [ 9.4 ]\n",
      " [13.48]\n",
      " [14.81]\n",
      " [ 6.31]\n",
      " [ 6.92]\n",
      " [13.64]\n",
      " [15.77]\n",
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      " [ 7.59]\n",
      " [13.03]\n",
      " [ 8.6 ]\n",
      " [13.58]\n",
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      " [13.27]\n",
      " [14.81]\n",
      " [13.41]\n",
      " [15.08]\n",
      " [10.16]]\n",
      "<NDArray 82x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 16.575951\n",
      "epoch 2, loss 8.904679\n",
      "epoch 3, loss 8.193842\n",
      "epoch 4, loss 8.127611\n",
      "epoch 5, loss 8.121077\n",
      "epoch 6, loss 8.120071\n",
      "epoch 7, loss 8.119576\n",
      "epoch 8, loss 8.119130\n",
      "epoch 9, loss 8.118688\n",
      "epoch 10, loss 8.118247\n",
      "epoch 11, loss 8.117805\n",
      "epoch 12, loss 8.117365\n",
      "epoch 13, loss 8.116923\n",
      "epoch 14, loss 8.116482\n",
      "epoch 15, loss 8.116041\n",
      "epoch 16, loss 8.115600\n",
      "epoch 17, loss 8.115159\n",
      "epoch 18, loss 8.114718\n",
      "epoch 19, loss 8.114277\n",
      "epoch 20, loss 8.113835\n",
      "epoch 21, loss 8.113397\n",
      "epoch 22, loss 8.112955\n",
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      "epoch 24, loss 8.112074\n",
      "epoch 25, loss 8.111633\n",
      "epoch 26, loss 8.111192\n",
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      "epoch 29, loss 8.109870\n",
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      "epoch 34, loss 8.107669\n",
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      "epoch 37, loss 8.106349\n",
      "epoch 38, loss 8.105908\n",
      "epoch 39, loss 8.105469\n",
      "epoch 40, loss 8.105029\n",
      "epoch 41, loss 8.104589\n",
      "epoch 42, loss 8.104148\n",
      "epoch 43, loss 8.103709\n",
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      "epoch 46, loss 8.102390\n",
      "epoch 47, loss 8.101950\n",
      "epoch 48, loss 8.101511\n",
      "epoch 49, loss 8.101070\n",
      "epoch 50, loss 8.100633\n",
      "epoch 51, loss 8.100193\n",
      "epoch 52, loss 8.099753\n",
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      "epoch 55, loss 8.098436\n",
      "epoch 56, loss 8.097996\n",
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      "epoch 58, loss 8.097118\n",
      "epoch 59, loss 8.096679\n",
      "epoch 60, loss 8.096240\n",
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      "epoch 87, loss 8.084407\n",
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      "epoch 131, loss 8.065198\n",
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      "epoch 157, loss 8.053890\n",
      "epoch 158, loss 8.053456\n",
      "epoch 159, loss 8.053021\n",
      "epoch 160, loss 8.052588\n",
      "epoch 161, loss 8.052154\n",
      "epoch 162, loss 8.051720\n",
      "epoch 163, loss 8.051286\n",
      "epoch 164, loss 8.050852\n",
      "epoch 165, loss 8.050418\n",
      "epoch 166, loss 8.049984\n",
      "epoch 167, loss 8.049550\n",
      "epoch 168, loss 8.049117\n",
      "epoch 169, loss 8.048683\n",
      "epoch 170, loss 8.048250\n",
      "epoch 171, loss 8.047816\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 172, loss 8.047382\n",
      "epoch 173, loss 8.046948\n",
      "epoch 174, loss 8.046515\n",
      "epoch 175, loss 8.046082\n",
      "epoch 176, loss 8.045649\n",
      "epoch 177, loss 8.045215\n",
      "epoch 178, loss 8.044781\n",
      "epoch 179, loss 8.044349\n",
      "epoch 180, loss 8.043915\n",
      "epoch 181, loss 8.043483\n",
      "epoch 182, loss 8.043049\n",
      "epoch 183, loss 8.042616\n",
      "epoch 184, loss 8.042183\n",
      "epoch 185, loss 8.041750\n",
      "epoch 186, loss 8.041317\n",
      "epoch 187, loss 8.040884\n",
      "epoch 188, loss 8.040451\n",
      "epoch 189, loss 8.040018\n",
      "epoch 190, loss 8.039586\n",
      "epoch 191, loss 8.039153\n",
      "epoch 192, loss 8.038720\n",
      "epoch 193, loss 8.038288\n",
      "epoch 194, loss 8.037856\n",
      "epoch 195, loss 8.037423\n",
      "epoch 196, loss 8.036991\n",
      "epoch 197, loss 8.036558\n",
      "epoch 198, loss 8.036126\n",
      "epoch 199, loss 8.035693\n",
      "epoch 200, loss 8.035261\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.3607178 ]\n",
      " [0.46315053]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.03765213]\n",
      "<NDArray 1 @cpu(0)>\n",
      "12\n",
      "[80, 80, 80, 80, 80, 80, 80, 80, 40, 80, 74, 82, 44]\n",
      "80\n",
      "\n",
      "[[ 9.25 23.44]\n",
      " [ 9.23 23.29]\n",
      " [ 9.22 23.29]\n",
      " [ 9.18 23.44]\n",
      " [ 9.28 23.29]\n",
      " [ 9.27 23.29]\n",
      " [ 9.19 23.29]\n",
      " [ 9.27 23.59]\n",
      " [ 9.18 23.14]\n",
      " [ 9.23 23.14]\n",
      " [ 9.26 23.44]\n",
      " [ 9.18 23.59]\n",
      " [ 9.19 23.14]\n",
      " [ 9.22 23.59]\n",
      " [ 9.24 23.44]\n",
      " [ 9.22 23.14]\n",
      " [ 9.26 23.59]\n",
      " [ 9.29 23.59]\n",
      " [ 9.18 23.29]\n",
      " [ 9.3  23.14]\n",
      " [ 9.26 23.14]\n",
      " [ 9.3  23.29]\n",
      " [ 9.23 23.44]\n",
      " [ 9.24 23.59]\n",
      " [ 9.25 23.59]\n",
      " [ 9.28 23.14]\n",
      " [ 9.29 23.44]\n",
      " [ 9.25 23.29]\n",
      " [ 9.26 23.29]\n",
      " [ 9.19 23.44]\n",
      " [ 9.28 23.59]\n",
      " [ 9.27 23.44]\n",
      " [ 9.22 23.44]\n",
      " [ 9.23 23.59]\n",
      " [ 9.3  23.59]\n",
      " [ 9.24 23.14]\n",
      " [ 9.29 23.29]\n",
      " [ 9.27 23.14]\n",
      " [ 9.3  23.44]\n",
      " [ 9.28 23.44]\n",
      " [ 9.29 23.14]\n",
      " [ 9.25 23.14]\n",
      " [ 9.19 23.59]\n",
      " [ 9.24 23.29]]\n",
      "<NDArray 44x2 @cpu(0)> \n",
      "[[ 4.7 ]\n",
      " [ 4.96]\n",
      " [ 4.06]\n",
      " [ 7.37]\n",
      " [ 6.34]\n",
      " [ 7.57]\n",
      " [ 5.3 ]\n",
      " [ 7.07]\n",
      " [23.9 ]\n",
      " [ 5.99]\n",
      " [ 6.38]\n",
      " [ 5.52]\n",
      " [ 5.35]\n",
      " [ 3.75]\n",
      " [ 3.57]\n",
      " [ 6.46]\n",
      " [ 5.69]\n",
      " [ 7.12]\n",
      " [ 8.59]\n",
      " [11.13]\n",
      " [20.23]\n",
      " [ 9.3 ]\n",
      " [ 3.69]\n",
      " [ 3.82]\n",
      " [ 4.61]\n",
      " [ 8.21]\n",
      " [ 8.3 ]\n",
      " [ 4.71]\n",
      " [18.9 ]\n",
      " [ 5.57]\n",
      " [17.45]\n",
      " [ 7.46]\n",
      " [ 3.66]\n",
      " [ 4.36]\n",
      " [ 7.04]\n",
      " [ 5.07]\n",
      " [ 9.01]\n",
      " [ 7.16]\n",
      " [ 8.93]\n",
      " [18.15]\n",
      " [ 9.14]\n",
      " [ 8.69]\n",
      " [ 6.94]\n",
      " [ 6.21]]\n",
      "<NDArray 44x1 @cpu(0)>\n",
      "oooooo1\n",
      "epoch 1, loss 20.431862\n",
      "epoch 2, loss 14.126240\n",
      "epoch 3, loss 11.986054\n",
      "epoch 4, loss 11.259651\n",
      "epoch 5, loss 11.013099\n",
      "epoch 6, loss 10.929412\n",
      "epoch 7, loss 10.901003\n",
      "epoch 8, loss 10.891356\n",
      "epoch 9, loss 10.888077\n",
      "epoch 10, loss 10.886958\n",
      "epoch 11, loss 10.886574\n",
      "epoch 12, loss 10.886437\n",
      "epoch 13, loss 10.886387\n",
      "epoch 14, loss 10.886364\n",
      "epoch 15, loss 10.886352\n",
      "epoch 16, loss 10.886344\n",
      "epoch 17, loss 10.886333\n",
      "epoch 18, loss 10.886328\n",
      "epoch 19, loss 10.886318\n",
      "epoch 20, loss 10.886312\n",
      "epoch 21, loss 10.886304\n",
      "epoch 22, loss 10.886296\n",
      "epoch 23, loss 10.886289\n",
      "epoch 24, loss 10.886280\n",
      "epoch 25, loss 10.886273\n",
      "epoch 26, loss 10.886266\n",
      "epoch 27, loss 10.886257\n",
      "epoch 28, loss 10.886250\n",
      "epoch 29, loss 10.886243\n",
      "epoch 30, loss 10.886235\n",
      "epoch 31, loss 10.886228\n",
      "epoch 32, loss 10.886219\n",
      "epoch 33, loss 10.886211\n",
      "epoch 34, loss 10.886204\n",
      "epoch 35, loss 10.886197\n",
      "epoch 36, loss 10.886189\n",
      "epoch 37, loss 10.886182\n",
      "epoch 38, loss 10.886174\n",
      "epoch 39, loss 10.886166\n",
      "epoch 40, loss 10.886159\n",
      "epoch 41, loss 10.886150\n",
      "epoch 42, loss 10.886143\n",
      "epoch 43, loss 10.886135\n",
      "epoch 44, loss 10.886127\n",
      "epoch 45, loss 10.886120\n",
      "epoch 46, loss 10.886112\n",
      "epoch 47, loss 10.886105\n",
      "epoch 48, loss 10.886097\n",
      "epoch 49, loss 10.886089\n",
      "epoch 50, loss 10.886082\n",
      "epoch 51, loss 10.886074\n",
      "epoch 52, loss 10.886066\n",
      "epoch 53, loss 10.886059\n",
      "epoch 54, loss 10.886051\n",
      "epoch 55, loss 10.886044\n",
      "epoch 56, loss 10.886036\n",
      "epoch 57, loss 10.886028\n",
      "epoch 58, loss 10.886021\n",
      "epoch 59, loss 10.886013\n",
      "epoch 60, loss 10.886005\n",
      "epoch 61, loss 10.885998\n",
      "epoch 62, loss 10.885990\n",
      "epoch 63, loss 10.885983\n",
      "epoch 64, loss 10.885975\n",
      "epoch 65, loss 10.885967\n",
      "epoch 66, loss 10.885960\n",
      "epoch 67, loss 10.885952\n",
      "epoch 68, loss 10.885944\n",
      "epoch 69, loss 10.885937\n",
      "epoch 70, loss 10.885929\n",
      "epoch 71, loss 10.885921\n",
      "epoch 72, loss 10.885914\n",
      "epoch 73, loss 10.885906\n",
      "epoch 74, loss 10.885899\n",
      "epoch 75, loss 10.885891\n",
      "epoch 76, loss 10.885883\n",
      "epoch 77, loss 10.885876\n",
      "epoch 78, loss 10.885868\n",
      "epoch 79, loss 10.885860\n",
      "epoch 80, loss 10.885853\n",
      "epoch 81, loss 10.885844\n",
      "epoch 82, loss 10.885837\n",
      "epoch 83, loss 10.885830\n",
      "epoch 84, loss 10.885822\n",
      "epoch 85, loss 10.885813\n",
      "epoch 86, loss 10.885806\n",
      "epoch 87, loss 10.885798\n",
      "epoch 88, loss 10.885791\n",
      "epoch 89, loss 10.885783\n",
      "epoch 90, loss 10.885776\n",
      "epoch 91, loss 10.885769\n",
      "epoch 92, loss 10.885761\n",
      "epoch 93, loss 10.885753\n",
      "epoch 94, loss 10.885745\n",
      "epoch 95, loss 10.885737\n",
      "epoch 96, loss 10.885731\n",
      "epoch 97, loss 10.885723\n",
      "epoch 98, loss 10.885715\n",
      "epoch 99, loss 10.885707\n",
      "epoch 100, loss 10.885700\n",
      "epoch 101, loss 10.885692\n",
      "epoch 102, loss 10.885685\n",
      "epoch 103, loss 10.885676\n",
      "epoch 104, loss 10.885669\n",
      "epoch 105, loss 10.885660\n",
      "epoch 106, loss 10.885653\n",
      "epoch 107, loss 10.885646\n",
      "epoch 108, loss 10.885638\n",
      "epoch 109, loss 10.885632\n",
      "epoch 110, loss 10.885622\n",
      "epoch 111, loss 10.885615\n",
      "epoch 112, loss 10.885608\n",
      "epoch 113, loss 10.885600\n",
      "epoch 114, loss 10.885592\n",
      "epoch 115, loss 10.885584\n",
      "epoch 116, loss 10.885577\n",
      "epoch 117, loss 10.885570\n",
      "epoch 118, loss 10.885562\n",
      "epoch 119, loss 10.885554\n",
      "epoch 120, loss 10.885547\n",
      "epoch 121, loss 10.885539\n",
      "epoch 122, loss 10.885531\n",
      "epoch 123, loss 10.885524\n",
      "epoch 124, loss 10.885516\n",
      "epoch 125, loss 10.885508\n",
      "epoch 126, loss 10.885501\n",
      "epoch 127, loss 10.885492\n",
      "epoch 128, loss 10.885486\n",
      "epoch 129, loss 10.885477\n",
      "epoch 130, loss 10.885469\n",
      "epoch 131, loss 10.885462\n",
      "epoch 132, loss 10.885454\n",
      "epoch 133, loss 10.885448\n",
      "epoch 134, loss 10.885438\n",
      "epoch 135, loss 10.885431\n",
      "epoch 136, loss 10.885424\n",
      "epoch 137, loss 10.885416\n",
      "epoch 138, loss 10.885408\n",
      "epoch 139, loss 10.885401\n",
      "epoch 140, loss 10.885394\n",
      "epoch 141, loss 10.885386\n",
      "epoch 142, loss 10.885378\n",
      "epoch 143, loss 10.885370\n",
      "epoch 144, loss 10.885362\n",
      "epoch 145, loss 10.885356\n",
      "epoch 146, loss 10.885347\n",
      "epoch 147, loss 10.885340\n",
      "epoch 148, loss 10.885333\n",
      "epoch 149, loss 10.885324\n",
      "epoch 150, loss 10.885318\n",
      "epoch 151, loss 10.885309\n",
      "epoch 152, loss 10.885302\n",
      "epoch 153, loss 10.885295\n",
      "epoch 154, loss 10.885286\n",
      "epoch 155, loss 10.885279\n",
      "epoch 156, loss 10.885271\n",
      "epoch 157, loss 10.885263\n",
      "epoch 158, loss 10.885255\n",
      "epoch 159, loss 10.885248\n",
      "epoch 160, loss 10.885241\n",
      "epoch 161, loss 10.885233\n",
      "epoch 162, loss 10.885226\n",
      "epoch 163, loss 10.885217\n",
      "epoch 164, loss 10.885210\n",
      "epoch 165, loss 10.885201\n",
      "epoch 166, loss 10.885194\n",
      "epoch 167, loss 10.885188\n",
      "epoch 168, loss 10.885180\n",
      "epoch 169, loss 10.885172\n",
      "epoch 170, loss 10.885163\n",
      "epoch 171, loss 10.885156\n",
      "epoch 172, loss 10.885148\n",
      "epoch 173, loss 10.885140\n",
      "epoch 174, loss 10.885134\n",
      "epoch 175, loss 10.885125\n",
      "epoch 176, loss 10.885118\n",
      "epoch 177, loss 10.885110\n",
      "epoch 178, loss 10.885102\n",
      "epoch 179, loss 10.885096\n",
      "epoch 180, loss 10.885088\n",
      "epoch 181, loss 10.885080\n",
      "epoch 182, loss 10.885072\n",
      "epoch 183, loss 10.885064\n",
      "epoch 184, loss 10.885057\n",
      "epoch 185, loss 10.885049\n",
      "epoch 186, loss 10.885041\n",
      "epoch 187, loss 10.885034\n",
      "epoch 188, loss 10.885026\n",
      "epoch 189, loss 10.885018\n",
      "epoch 190, loss 10.885012\n",
      "epoch 191, loss 10.885003\n",
      "epoch 192, loss 10.884995\n",
      "epoch 193, loss 10.884988\n",
      "epoch 194, loss 10.884980\n",
      "epoch 195, loss 10.884973\n",
      "epoch 196, loss 10.884965\n",
      "epoch 197, loss 10.884958\n",
      "epoch 198, loss 10.884950\n",
      "epoch 199, loss 10.884942\n",
      "epoch 200, loss 10.884934\n",
      "oooooo1\n",
      "权重参数为\n",
      "\n",
      "[[0.13761078]\n",
      " [0.2826203 ]]\n",
      "<NDArray 2x1 @cpu(0)>\n",
      "常数差值为\n",
      "\n",
      "[0.01284445]\n",
      "<NDArray 1 @cpu(0)>\n"
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   "source": [
    "%matplotlib inline\n",
    "from IPython import display\n",
    "from matplotlib import pyplot as plt\n",
    "from mxnet import autograd, nd\n",
    "import datetime\n",
    "import random\n",
    "\n",
    "import cx_Oracle\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "day=10*96       #模拟的天数*96   一天96个数据\n",
    "#time1=3        #  模拟的第x个时间段  共有7个时间段\n",
    "\n",
    "many_segment = 13       #将时间分为x段\n",
    "time_segment=nd.zeros((many_segment,2))    \n",
    "time_segment=nd.array([[0,1],[2,3],[4,5],[6,7],[8,9],[10,11],[12,13],[14,15],[15,16],[17,18],[19,20],[21,22],[23,24]])  #每一段时间的储存点\n",
    "time_size=[0,0,0,0,0,0,0,0,0,0,0,0,0]    #每段时间的数据样本数量\n",
    "\n",
    "print (\"运行中---------\")\n",
    "\n",
    "#def get_week_day(date):\n",
    "    \n",
    " # week_day = {\n",
    "#        0: '星期一',\n",
    "#        1: '星期二',\n",
    "#        2: '星期三',\n",
    "#       3: '星期四',\n",
    "#        4: '星期五',\n",
    "#        5: '星期六',\n",
    "#        6: '星期日',\n",
    "#    } \n",
    " \n",
    "#    day = date.weekday() #weekday()可以获得是星期几\n",
    "#    return  day\n",
    "\n",
    "tns = cx_Oracle.makedsn('192.168.0.61',1521,'orcl')\n",
    "db = cx_Oracle.connect('test','123',tns)\n",
    "cur = db.cursor()\n",
    "sql = '''SELECT * FROM ODBC_IMPORT1'''\n",
    "cur.execute(sql)\n",
    "  \n",
    "\n",
    "\n",
    "#f = open('D:\\deep-learning\\d2l-zh\\work\\data.txt')      #打开数据文件\n",
    "\n",
    "\n",
    "\n",
    "         \n",
    "for num in range(0,day):\n",
    "        #temp=f.readline()\n",
    "        #temp = cur.fetchone()\n",
    "        #val=temp.split()\n",
    "    val=cur.fetchone()\n",
    "    if val == None:        \n",
    "        break\n",
    "        #hei=val[2].split('/')\n",
    "    date_temp=val[2].split()\n",
    "    hei=date_temp[0].split('/')\n",
    "        #someday=datetime.date(int(hei[0]),int(hei[1]),int(hei[2])).weekday() \n",
    "        #aq=val[3].split(':')\n",
    "    aq=date_temp[1].split(':')\n",
    "    num2=0\n",
    "    for num2 in range(0,many_segment):\n",
    "        if float(aq[0])<=time_segment[num2,1] and float(aq[0])>=time_segment[num2,0]:       \n",
    "            time_size[num2]+=1\n",
    "            \n",
    "            #print()\n",
    "            break\n",
    "\n",
    "    \n",
    "#f.close()\n",
    "cur.close()\n",
    "\n",
    "tns = cx_Oracle.makedsn('192.168.0.61',1521,'orcl')\n",
    "db = cx_Oracle.connect('test','123',tns)\n",
    "cur = db.cursor()\n",
    "for which in range(0,many_segment):\n",
    "    time1=which\n",
    "    print(time1)\n",
    "    print(time_size)\n",
    "    print(time_size[2])\n",
    "    num_inputs = 2         #特征值的个数\n",
    "    num_examples = time_size[which]    #数据样本容量\n",
    "    features = nd.zeros((num_examples, num_inputs))  #训练数据集\n",
    "    labels = nd.zeros((num_examples,1))             #标签集\n",
    "\n",
    "\n",
    "\n",
    "    #f = open('D:\\deep-learning\\d2l-zh\\work\\data.txt')      #打开数据文件\n",
    "    db = cx_Oracle.connect('test','123',tns)\n",
    "    cur = db.cursor()\n",
    "    sql = '''SELECT * FROM ODBC_IMPORT1'''\n",
    "    cur.execute(sql)\n",
    "    \n",
    "    numm=0\n",
    "    for num in range(0,day):\n",
    "        #temp=f.readline()\n",
    "        #val=temp.split()\n",
    "        #hei=val[2].split('/')       \n",
    "        #someday=datetime.date(int(hei[0]),int(hei[1]),int(hei[2])).weekday() \n",
    "        #aq=val[3].split(':')\n",
    "        \n",
    "        \n",
    "        val=cur.fetchone()\n",
    "        if val == None:        \n",
    "            break\n",
    "        #hei=val[2].split('/')\n",
    "        date_temp=val[2].split()\n",
    "        hei=date_temp[0].split('/')\n",
    "        #someday=datetime.date(int(hei[0]),int(hei[1]),int(hei[2])).weekday() u\n",
    "        #aq=val[3].split(':')\n",
    "        aq=date_temp[1].split(':')\n",
    "    \n",
    "    \n",
    "        \n",
    "        w=float(aq[0])+float(aq[1])/100\n",
    "    \n",
    "        if  float(aq[0])>time_segment[time1,1]or float(aq[0])<time_segment[time1,0]:\n",
    "            continue\n",
    "    \n",
    "    \n",
    "\n",
    "        #print(num1)\n",
    "        labels[numm]=float(val[1])\n",
    "\n",
    "        #features[num1,0]=float(someday+1)\n",
    "       # features[num1,0]=float(aq[0])\n",
    "        features[numm,0]=float(hei[1])+float(hei[2])/100\n",
    "\n",
    "        features[numm,1]=w\n",
    "    \n",
    "        if numm>=(num_examples-1):\n",
    "            break\n",
    "        numm+=1\n",
    "        \n",
    "        \n",
    "\n",
    "    #f.close()\n",
    "\n",
    "\n",
    "    def use_svg_display():\n",
    "    # 用矢量图显示\n",
    "        display.set_matplotlib_formats('svg')\n",
    "\n",
    "    def set_figsize(figsize=(3.5, 2.5)):\n",
    "        use_svg_display()\n",
    "    # 设置图的尺寸\n",
    "        plt.rcParams['figure.figsize'] = figsize\n",
    "\n",
    "\n",
    "    set_figsize()\n",
    "    plt.scatter(features[:, 1].asnumpy(), labels.asnumpy(), s=1,c=['b']);  # 加分号只显示图   预测结果显示\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# 本函数已保存在d2lzh包中方便以后使用\n",
    "    def data_iter(batch_size, features, labels):\n",
    "        num_examples = len(features)\n",
    "        indices = list(range(num_examples))\n",
    "        random.shuffle(indices)  # 样本的读取顺序是随机的\n",
    "        for i in range(0, num_examples, batch_size):\n",
    "            j = nd.array(indices[i: min(i + batch_size, num_examples)])\n",
    "            yield features.take(j), labels.take(j)  # take函数根据索引返回对应元素\n",
    "        \n",
    "        \n",
    "\n",
    "    batch_size = 200\n",
    "\n",
    "    for X, y in data_iter(batch_size, features, labels):\n",
    "        print(X, y)\n",
    "        break\n",
    "    \n",
    "    w = nd.random.normal(scale=0.01, shape=(num_inputs, 1))\n",
    "    b = nd.zeros(shape=(1,))\n",
    "\n",
    "    w.attach_grad()\n",
    "    b.attach_grad()\n",
    "\n",
    "\n",
    "    def linreg(X, w, b):  # 本函数已保存在d2lzh包中方便以后使用\n",
    "        return nd.dot(X, w) + b\n",
    "\n",
    "    def squared_loss(y_hat, y):  # 本函数已保存在d2lzh包中方便以后使用\n",
    "        return (y_hat - y.reshape(y_hat.shape)) ** 2 / 2\n",
    "\n",
    "\n",
    "    def sgd(params, lr, batch_size):  # 本函数已保存在d2lzh包中方便以后使用\n",
    "        for param in params:\n",
    "            param[:] = param - lr * param.grad / batch_size\n",
    "        \n",
    "\n",
    "    lr = 0.003       #学习率\n",
    "    num_epochs = 200  #迭代次数 \n",
    "    net = linreg\n",
    "    loss = squared_loss\n",
    "    print('oooooo1')\n",
    "    for epoch in range(num_epochs):  # 训练模型一共需要num_epochs个迭代周期\n",
    "    # 在每一个迭代周期中，会使用训练数据集中所有样本一次（假设样本数能够被批量大小整除）。X\n",
    "    # 和y分别是小批量样本的特征和标签\n",
    "        for X, y in data_iter(batch_size, features, labels):\n",
    "            with autograd.record():\n",
    "                l = loss(net(X, w, b), y)  # l是有关小批量X和y的损失\n",
    "            l.backward()  # 小批量的损失对模型参数求梯度\n",
    "            sgd([w, b], lr, batch_size)  # 使用小批量随机梯度下降迭代模型参数\n",
    "        train_l = loss(net(features, w, b), labels)\n",
    "        print('epoch %d, loss %f' % (epoch + 1, train_l.mean().asnumpy()))\n",
    "        \n",
    "    te_num_inputs = 2\n",
    "    te_num_examples = num_examples\n",
    "\n",
    "#    te_features = nd.random.normal(9.27,0.01, shape=(num_examples, 1))\n",
    "\n",
    "    \n",
    "#    te_features2 = nd.random.normal(10.5,1, shape=(num_examples, 1))\n",
    "#    te_features=nd.concat(te_features,te_features2,dim=1)\n",
    "\n",
    "\n",
    "    te_labels = w[0] * features[:, 0] + w[1] * features[:, 1] + b\n",
    "    te_labels += nd.random.normal(0,0.75, shape=te_labels.shape)\n",
    "\n",
    "\n",
    "    set_figsize()\n",
    "    plt.scatter(features[:, 1].asnumpy(), te_labels.asnumpy(), s=1,c=['m']);  # 加分号只显示图   预测结果显示\n",
    "    db.commit()\n",
    "\n",
    " # 关闭数据库\n",
    "    db.close()\n",
    "    \n",
    "    \n",
    "    dba = cx_Oracle.connect('test','123',tns)\n",
    "    cur1 = dba.cursor()\n",
    "    for a_num in range(0,te_num_examples):\n",
    "        \n",
    "        \n",
    "        a1=str(te_labels[a_num]).split('[')\n",
    "        a1a1=a1[1].split(']')\n",
    "        a1_a1=a1a1[0]\n",
    "        #print(a1_a1)\n",
    "\n",
    "        a2=str(features[a_num][0]).split('[')\n",
    "        a2a2=a2[1].split(']')\n",
    "        a2_a2=a2a2[0]\n",
    "        \n",
    "        a3=str(features[a_num][1]).split('[')\n",
    "        a3a3=a3[1].split(']')\n",
    "        a3_a3=a3a3[0]\n",
    "\n",
    "        sql ='INSERT INTO ODBC_IMPORT_STRING(流量,日期,时间) VALUES(\\''+a1_a1+'\\',\\''+a2_a2+'\\',\\''+a3_a3+'\\')'\n",
    "\n",
    "        cur1.execute(sql)\n",
    "    dba.commit()\n",
    "    dba.close()\n",
    "    \n",
    "#         print(features[a_num][0])\n",
    "#         print(features[a_num][1])\n",
    "\n",
    "    \n",
    "    \n",
    "    print('oooooo1')\n",
    "    print(\"权重参数为\")\n",
    "    print(w)\n",
    "    print('常数差值为')\n",
    "    print(b)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "inappropriate-truth",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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